Subcritical Hopf Bifurcation in the Delay Equation Model for Machine Tool Vibrations

Size: px
Start display at page:

Download "Subcritical Hopf Bifurcation in the Delay Equation Model for Machine Tool Vibrations"

Transcription

1 Nonlinear Dynamics 26: 2 42, 2. 2 Kluwer Academic Publishers. Printed in the Netherlands. Subcritical Hopf Bifurcation in the Delay Equation Model for Machine Tool Vibrations TAMÁS KALMÁR-NAGY Department of Theoretical and Applied Mechanics, Cornell University, Ithaca, NY 4853, U.S.A. GÁBOR STÉPÁN Department of Applied Mechanics, Technical University of Budapest, H-52 Budapest, Hungary FRANCIS C. MOON Sibley School of Aerospace & Mechanical Engineering, Cornell University, Ithaca, NY 4853, U.S.A. (Received: 9 April 998; accepted: 7 January 2) Abstract. We show the existence of a subcritical Hopf bifurcation in the delay-differential equation model of the so-called regenerative machine tool vibration. The calculation is based on the reduction of the infinite-dimensional problem to a two-dimensional center manifold. Due to the special algebraic structure of the delayed terms in the nonlinear part of the equation, the computation results in simple analytical formulas. Numerical simulations gave excellent agreement with the results. Keywords: Hopf bifurcation, delay differential equation, center manifold, chatter.. Introduction One of the most important effects causing poor surface quality in a cutting process is vibration arising from delay. Because of some external disturbances the tool starts a damped oscillation relative to the workpiece thus making its surface uneven. After one revolution of the workpiece the chip thickness will vary at the tool. The cutting force thus depends not only on the current position of the tool and the workpiece but also on a delayed value of the displacement. The length of this delay is the time-period τ of one revolution of the workpiece. This is the socalled regenerative effect (see, for example, [2, 6, 9, 2]). The corresponding mathematical model is a delay-differential equation. In order to study phenomena related to delay effects, a simple DOF model of the tool was considered. Even though the model has only DOF, the delay term makes the phase space infinite-dimensional. Experimental results of Shi and Tobias [5] and Kalmár-Nagy et al. [9] clearly showed the existence of finite amplitude instability, that is unstable periodic motion of the tool around its asymptotically stable position related to the stationary cutting. Recently, there has been increased interest in the subject. The Ph.D. theses of Johnson [8] and Fofana [4], and the paper of Nayfeh et al. [3] presented the analysis of the Hopf bifurcation in different models using different methods, like the method of multiple scales, harmonic balance, Floquet Theory (see also [4]) and of course, numerical simulations. New models have been proposed to explain chip segmentation by Burns and Davies []. This highfrequency process may also affect the tool dynamics. The aim of this paper is to give a rigorous analytical investigation of the Hopf bifurcation present in the regenerative machine tool vibration model using the theory and tools of the Hopf

2 22 T. Kalmár-Nagy et al. Figure. DOF mechanical model. Bifurcation Theorem and the Center Manifold Theorem. Although these have been available for a long time [5, 7] the closed form calculation regarding the existence and the nature of the corresponding Hopf bifurcation in the mathematical model is only feasible by using computer algebra (see also [2]). 2. Mechanical Model for Tool Vibrations Figure shows a DOF mechanical model of the regenerative machine tool vibration in the case of the so-called orthogonal cutting (f denotes chip thickness). The model is the simplest one which still explains the basic stability problems and nonlinear vibrations arising in this system [6 8]. The corresponding Free Body Diagram (ignoring horizontal forces) is also showninfigure.here l = l l + x(t) where l, l are the initial spring length and spring length in steady-state cutting, respectively. The zero value of the general coordinate x(t) of the tool edge position is set in a way that the x component F x of the cutting force F is in balance with the spring force when the chip thickness f is just the prescribed value f (steady-state cutting). The equation of motion of the tool is clearly mẍ = s l F x cẋ. () In steady-state cutting (x =ẋ =ẍ = ) = s(l l ) F x (f ) F x (f ) = s(l l ), i.e., there is pre-stress in the spring. If we write F x = F x (f )+ F x then Equation () becomes ẍ + 2ζω n ẋ + ω 2 n x = m F x, (2) where ω n = s/m is the natural angular frequency of the undamped free oscillating system, and ζ = c/(2mω n ) is the so-called relative damping factor. The calculation of the cutting force variation F x requires an expression of the cutting force as a function of the technological parameters, primarily as a function of the chip thickness f which depends on the position x of the tool edge. The traditional models [2, 2] use the cutting coefficient k derived from the stationary idea of the cutting force as an empirical function of the technological parameters like the chip width w, the chip thickness f, and the cutting speed v. A simple but empirical way to calculate the cutting force is using a curve fitted to data obtained from cutting tests. Shi and Tobias [5] gave a third-order polynomial for the cutting force (similar to Figure 2). The coefficient of the second-order term is negative which suggests

3 Subcritical Hopf Bifurcation in the Delay Equation Model 23 Figure 2. Cutting force and chip thickness relation. a simple power law with exponent less than. Here we will use the formula given by Taylor [8]. According to this, the cutting force F x depends on the chip thickness as F x (f ) = Kwf 3/4, where the parameter K depends on further technological parameters considered to be constant in the present analysis. Expanding F x into a power series form around the desired chip thickness f and keeping terms up to order 3 yields ( F x (f ) Kw f 3/ (f f )f / (f f ) 2 f 5/4 + 5 ) 28 (f f ) 3 f 9/4. Or, equivalently, we can express the cutting force variation F x = F x (f ) F x (f ) as the function of the chip thickness variation f = f f, like ( 3 F x ( f ) Kw 4 f /4 f 3 32 f 5/4 f ) 28 f 9/4 f 3. (3) The coefficient of f on the right-hand side of Equation (3) is usually called the cutting force coefficient and denoted by k (k = (3/4)Kwf /4 ). Note, that k is linearly proportional to the width w of the chip, so in the upcoming calculations it will serve as a bifurcation parameter. Then Equation (3) can be rewritten as k F x ( f ) k f f f 96 k f 2 f 3. Even though only the local bifurcation at f = f f = will be investigated in this study we mention the case when the tool leaves the material, that is f < f < f.inthis case F x ( f ) = F x (f ) and so the regenerative effect is switched off until the tool makes contact with the workpiece again. The chip thickness variation f can easily be expressed as the difference of the present tool edge position x(t) and the delayed one x(t τ) in the form f = x(t) x(t τ) = x x τ,

4 24 T. Kalmár-Nagy et al. where the delay τ = 2π/ is the time period of one revolution with being the constant angular velocity of the rotating workpiece. By bringing the linear terms to the left-hand side, Equation (2) becomes ẍ + 2ζω n ẋ + ( ωn 2 + k m ) x k m x τ = k ( (x x τ ) 2 5 (x x τ ) 3 8f m 2f ). Let us introduce the nondimensional time t and displacement x t = ω n t, x = 5 x, 2f and the nondimensional bifurcation parameter p = k /(mωn 2 ) (note that the nondimensional time delay is τ = ω n τ). Dropping the tilde we arrive at ẍ + 2ζ ẋ + ( + p)x px τ = 3p ((x x τ ) 2 (x x τ ) 3 ). This second-order equation is transformed into a two-dimensional system by introducing x(t) = ( x (t) x 2 (t) ) = ( x(t) ẋ(t) and we obtain the delay-differential equation ) ẋ(t) = L(p)x(t) + R(p)x(t τ)+ f(x(t), p), (4) where the dependence on the bifurcation parameter p is also emphasized: ( ) L(p) =, ( + p) 2ζ R(p) = ( ), p f(x(t), p) = 3p ( ) (x (t) x (t τ)) 2 (x (t) x (t τ)) 3. (5) 3. Linear Stability Analysis The characteristic function of Equation (4) can be obtained by substituting the trial solution x(t) = c exp(λt) into its linear part: D(λ,p) = det(λi L(p) R(p) e λτ ) = λ 2 + 2ζλ+ ( + p) p e λτ. (6)

5 Subcritical Hopf Bifurcation in the Delay Equation Model 25 Figure 3. Stability chart. The necessary condition for the existence of a nonzero solution is D(λ,p) =. On the stability boundary shown in Figure 3 the characteristic equation has one pair of pure imaginary roots (except the intersections of the lobes, where it has two pairs of imaginary roots). To find this curve, we substitute λ = iω, ω> into Equation (6). D(iω,p) = + p ω 2 p cos ωτ + i(2ζω+ p sin ωτ) =. This complex equation is equivalent to the two real equations ω 2 + p( cos ωτ) =, (7) 2ζω+ p sin ωτ =. (8) The trigonometric terms in Equations (7) and (8) can be eliminated to yield p = ( ω2 ) 2 + 4ζ 2 ω 2. 2(ω 2 ) Since p>this also implies ω>. With the help of the trigonometric identity cos ωτ sin ωτ = tan ωτ 2 τ can be expressed from Equations (7) and (8) as τ = 2 ( ) jπ arctan ω2, j =, 2,..., ω 2ζω where j corresponds to the jth lobe (parameterized by ω) from the right in the stability diagram (j must be greater than, because τ>). And finally = 2π τ = ωπ, j =, 2,... jπ arctan ω2 2ζω

6 26 T. Kalmár-Nagy et al. At the minima ( notches ) of the stability boundary ω, p, assume particularly simple forms. To find these values dp/dω = has to be solved. Then we find ω = + 2ζ, p = 2ζ(ζ + ), τ = = ( 2 ) +2ζ jπ arctan + 2ζ, j =, 2,..., + 2ζπ, j =, 2,... (9) jπ arctan +2ζ To simplify calculations we present results obtained at these parameter values (the calculations can be carried out in general along the stability boundary, see []). The location of the characteristic roots has now to be established. For p = Equation (6) has only two roots (λ,2 = ζ ± i ζ 2 ) and these are located in the left half plane. Increasing the value of p results in characteristic roots swarming out from minus complex infinity (the north pole of the Riemann-sphere). So for small p all the characteristic roots are in the left half plane (this can be proved with Rouché s Theorem, see []). The necessary condition for the existence of periodic orbits is that by varying the bifurcation parameter (p) the critical characteristic roots cross the imaginary axis with nonzero velocity, that is Re dλ(p cr) =. dp The characteristic function (6) has two zeros λ =±i + 2ζ at the notches. The change of the real parts of these critical characteristic roots can be determined via implicit differentiation of the characteristic function (6) with respect to the bifurcation parameter p dd(λ(p),p) dp dλ(p cr ) dp = D(λ(p),p) p D(λ(p),p) p =, λ=i +2ζ γ := Re dλ(p cr) dp D(λ(p),p) λ = + D(λ(p),p) dλ(p) λ dp =, 2( + ζ) 2 ( + ζτ). () Since γ is always positive and all the characteristic roots but the critical ones of (6) are located in the left half complex plane, the conditions of an infinite-dimensional version of the Hopf Bifurcation Theorem given in [7] are satisfied. γ will later be used in the estimation of the vibration amplitude. 4. Operator Differential Equation Formulation In order to study the critical infinite-dimensional problem on a two-dimensional center manifold we need the operator differential equation representation of Equation (4).

7 Subcritical Hopf Bifurcation in the Delay Equation Model 27 This delay-differential equation can be expressed as the abstract evolution equation [2, 6, ] on the Banach space H of continuously differentiable functions u :[ τ,] R 2 ẋ t = Ax t + F (x t ). () Here x t (ϕ) H is defined by the shift of time x t (ϕ) = x(t + ϕ), ϕ [ τ,]. (2) The linear operator A at the critical value of the bifurcation parameter assumes the form Au(ϑ) = { d dϑ u(ϑ), ϑ [ τ,), Lu() + Ru( τ), ϑ =, while the nonlinear operator F can be written as ( F (u)(ϑ) =, ) ϑ [ τ,),, ϑ =, 3p (u () u ( τ)) 2 (u () u ( τ)) 3 where u H (cf. Equation (5)). The adjoint space H of continuously differentiable functions v :[,τ] R 2 with the adjoint operator { A d v(σ ), v(σ ) = dσ σ (,τ], L v() + R v(τ), σ =, is also needed as well as the bilinear form (, ): H H R defined by (v, u) = v ()u() + τ v (ξ + τ)ru(ξ) dξ. (3) The formal adjoint and the bilinear form provide the basis for a geometry in which it is possible to develop a projection using the basis eigenvectors of the formal adjoint. The significance of this projection is that the critical delay system has a two-dimensional attractive subsystem (the center manifold) and the solutions on this manifold determine the long time behavior of the full system. For a heuristic argument of how these operators and bilinear form arise, see the Appendix. The mathematically inclined can study [6]. Since the critical eigenvalues of the linear operator A just coincide with the critical characteristic roots of the characteristic function D(λ,p), the Hopf bifurcation arising at the degenerate trivial solution can be studied on a two-dimensional center manifold embedded in the infinite-dimensional phase space. A first-order approximation to this center manifold can be given by the center subspace of the associated linear problem, which is spanned by the real and imaginary parts s, s 2 of the complex eigenfunction s(ϑ) H corresponding to the critical characteristic root iω.this eigenfunction satisfies that is As(ϑ) = iωs(ϑ), A(s (ϑ) + is 2 (ϑ)) = iω(s (ϑ) + is 2 (ϑ)).

8 28 T. Kalmár-Nagy et al. Separating the real and imaginary parts yields As (ϑ) = ωs 2 (ϑ), As 2 (ϑ) = ωs (ϑ). Using the definition of A results the following boundary value problem d dϑ s (ϑ) = ωs 2 (ϑ), d dϑ s 2(ϑ) = ωs (ϑ), (4) Ls () + Rs ( τ) = ωs 2 (), Ls 2 () + Rs 2 ( τ) = ωs (). (5) The general solution to the differential equation (4) is s (ϑ) = cos(ωϑ)c sin(ωϑ)c 2, s 2 (ϑ) = sin(ωϑ)c + cos(ωϑ)c 2. The boundary conditions (5) result in a system of linear equations for some of the unknown coefficients: ( ) ( ) c L + cos(ωτ)r ωi + sin(ωτ)r =. (6) c 2 The center manifold reduction also requires the calculation of the left-hand side critical real eigenfunctions n,2 of A that satisfy the adjoint problem A n (σ ) = ωn 2 (σ ), A n 2 (σ ) = ωn (σ ). This boundary value problem has the general solution n (σ ) = cos(ωσ )d sin(ωσ )d 2, n 2 (σ ) = sin(ωσ )d + cos(ωσ )d 2, while the boundary conditions simplify to ( L T + cos(ωτ)r T ωi sin(ωτ)r T ) ( ) d =. (7) d 2 With the help of the bilinear form (3), the orthonormality conditions (n, s ) =, (n, s 2 ) = (8) provide two more equations.

9 Subcritical Hopf Bifurcation in the Delay Equation Model 29 Since Equations (6 8) do not determine the unknown coefficients uniquely (8 unknowns and 6 equations) we can choose two of them freely (so that the others will be of simple form) c =, c 2 =. Then ( ) ( ) c =, c 2 =, ω ( 2ζ 2 ) ( ) + 2ζ + ζ d = 2γ, d 2 = 2γω. ζ Let us decompose the solution x t (ϑ) of Equation () into two components y,2 lying in the center subspace and into the infinite-dimensional component w transverse to the center subspace: where x t (ϑ) = y (t)s (ϑ) + y 2 (t)s 2 (ϑ) + w(t)(ϑ), (9) y (t) = (n, x t ) ϑ=, y 2 (t) = (n 2, x t ) ϑ=. With these new coordinates the operator differential equation () can be transformed into a canonical form (see the Appendix) where ẏ = (n, ẋ t ) = ωy 2 + n T ()F, (2) ẏ 2 = (n 2, ẋ t ) = ωy + n T 2 ()F, (2) ẇ = Aw + F (x t ) n T ()Fs n T 2 ()Fs 2, (22) F = F (y (t)s () + y 2 (t)s 2 () + w(t)()) and in Equation (22) the decomposition (9) should be substituted for x t. Equations (4) and (5) give rise to the nonlinear operator F (w + y s + y 2 s 2 )(ϑ), ϑ [ τ,), ( ) = 3 5 ζz ( ) 2 z +ζ + 2(w z, ϑ =, () w ( τ)) +ζ where z = y ωy 2 and the terms of fourth or higher order were neglected (since w(y,y 2 ) is second order in Equation (24) and the normal form (35) will only contain terms up to third order). (23)

10 3 T. Kalmár-Nagy et al. 5. Two-Dimensional Center Manifold The center manifold is tangent to the plane y,y 2 at the origin, and it is locally invariant and attractive to the flow of system (). Since the nonlinearities considered here are nonsymmetric, we have to compute the second-order Taylor-series expansion of the center manifold. Thus, its equation can be assumed in the form of the truncated power series w(y,y 2 )(ϑ) = 2 (h (ϑ)y 2 + 2h 2(ϑ)y y 2 + h 3 (ϑ)y2 2 ). (24) The time derivative of w can be expressed both by differentiating the right-hand side of Equation (24) via substituting Equations (2) and (2) ẇ = h y ẏ + h 2 y 2 ẏ + h 2 y ẏ 2 + h 3 y 2 ẏ 2 = ẏ (h y + h 2 y 2 ) +ẏ 2 (h 2 y + h 3 y 2 ) = (ωy 2 + d 2 f)(h y + h 2 y 2 ) + ( ωy + d 22 f)(h 2 y + h 3 y 2 ) = ωh 2 y 2 + ω(h h 3 )y y 2 + ωh 2 y o(y3 ), where f = ( ) F and also by calculating Equation (22) dw = Aw + F (w + y s + y 2 s 2 ) (d 2 s + d 22 s 2 ) f, dt where { 2 Aw = (ḣ y 2 + 2ḣ 2 y y 2 + ḣ 3 y2 2 ), ϑ [ τ,), Lw() + Rw( τ), ϑ =, Lw() + Rw( τ) = 2 y2 (Lh () + Rh ( τ)) + y y 2 (Lh 2 () + Rh 2 ( τ))+ 2 y2 2 (Lh 3() + Rh 3 ( τ)). Equating like coefficients of the second degree expressions y 2, y y 2, y2 2 we obtain a sixdimensional linear boundary value problem for the unknown coefficients h, h 2, h 3 2ḣ = ωh 2 + f (d 2 s (ϑ) + d 22 s 2 (ϑ)), ḣ 2 = ωh ωh 3 + f 2 (d 2 s (ϑ) + d 22 s 2 (ϑ)), = ωh 2 + f 22 (d 2 s (ϑ) + d 22 s 2 (ϑ)), (25) 2ḣ3 2 (Lh () + Rh ( τ)) = ωh 2 () + f (d 2 s () + d 22 s 2 ()), Lh 2 () + Rh 2 ( τ) = ωh () ωh 3 () + f 2 (d 2 s () + d 22 s 2 ()), 2 (Lh 3() + Rh 3 ( τ)) = ωh 2 () + f 22 (d 2 s () + d 22 s 2 ()), (26)

11 Subcritical Hopf Bifurcation in the Delay Equation Model 3 where the f ij s denote the partial derivatives of f (with the appropriate multiplier) evaluated at y = y 2 = (thus giving the coefficient of the corresponding quadratic term) f = 2 f 2 y 2, f 2 = 2 f y y, f 22 = 2 f 2 2 y2 2. Introducing the following notation h 2I h := h 2, C 6 6 = ω I I, h 3 2I p = p = f p f 2 p, q = f 22 p ( d2 c 22 d 22 f q f 2 q, f 22 q ) ( ) d22, q =. c 22 d 2 Equation (25) can be written as the inhomogeneous differential equation d h = Ch + p cos(ωϑ) + q sin(ωϑ). (27) dϑ The general solution of Equation (27) assumes the usual form h(ϑ) = e Cϑ K + M cos(ωϑ) + N sin(ωϑ). (28) The coefficients M, N of the nonhomogeneous part are obtained after substituting this solution back to Equation (27) resulting in a 2-dimensional inhomogeneous linear algebraic system ( )( ) ( ) C6 6 ωi 6 6 M p =. (29) ωi 6 6 C 6 6 N q Since we will only need the first component w of w(y,y 2 )(ϑ) (see Equation (23)) we have to calculate only the first, third and fifth component of M, N, K. From Equation (29) M ω(3 + 2ζ 5( + ζ)ω M 3 = 2ζ 2 + 2ζ +, (3) 4ζγ M 5 ω(3 + 4ζ) N 2 + 7ζ + 4ζ 2 5( + ζ)ω N 3 = ζω. (3) 4ζγ N 5 2ζ 2 ζ 2 The boundary condition for h associated with Equation (27) comes from those parts of Equation (22) where A, F are defined at ϑ =. It is Ph() + Qh( τ) = p + r (32)

12 32 T. Kalmár-Nagy et al. with P 6 6 = L L C 6 6, Q 6 6 = L R R, R r = ( f f 2 f 22 ) T. K is found by substituting the general solution (28) into Equation (32) (P + Q e τc )K = r + p PM Q(cos(ωτ)M sin(ωτ)n). (33) Despite its hideous look Equation (33) simplifies, because p PM Q(cos(ωτ)M sin(ωτ)n) =. For our system K ζ + 32ζ 2 K 3 6ζ = ω(3 + 4ζ). (34) 5(9 + 33ζ + 32ζ K 2 ) ζ + 32ζ 2 Finally, Equations (3, 3, 34) are substituted into Equation (28) resulting in the secondorder approximation of the center manifold (24). It is not necessary to express the center manifold approximation in its full form, since we only need the values of its components at ϑ = and τ in the transformed operator equation (2, 2, 22). For example, w () = 2 ((M + K )y 2 + 2(M 3 + K 3 )y y 2 + (M 5 + K 5 )y 2 2 ), while the expression for w ( τ) is somewhat more lengthy. 6. The Hopf Bifurcation In order to restrict a third-order approximation of system (2 22) to the two-dimensional center manifold calculated in the previous section, the second-order approximation w(y,y 2 ) of the center manifold has to be substituted into the two scalar equations (2) and (2). Then these equations will assume the form ẏ = ωy 2 + a 2 y 2 + a y y 2 + a 2 y a 3y 3 + a 2y 2 y 2 + a 2 y y a 3y 3 2, ẏ 2 = ωy + b 2 y 2 + b y y 2 + b 2 y b 3y 3 + b 2y 2 y 2 + b 2 y y b 3y 3 2. (35) Using out of these 4 coefficients a jk,b jk, the so-called Poincaré Lyapunov constant can be calculated as shown in [5] or [7] = 8ω [(a 2 + a 2 )( a + b 2 b 2 ) + (b 2 + b 2 )(a 2 a 2 + b )] + 8 (3a 3 + a 2 + b 2 + 3b 3 ).

13 Subcritical Hopf Bifurcation in the Delay Equation Model 33 The negative/positive sign of determines if the Hopf bifurcation is supercritical or subcritical. Despite the above described tedious calculations is quite simple: = 9ζγ ζ + 96ζ ζ ζ + 32ζ 2 >. This means that the Hopf bifurcation is subcritical, thatisunstable periodic motion exists around the stable steady state cutting for cutting coefficients p which are somewhat smaller than the critical value p cr. This unstable limit cycle determines the domain of attraction of the asymptotically stable stationary cutting. The estimation of the vibration amplitude has the simple form r = γ (p p γpcr cr) = p. p cr The approximation of the corresponding periodic solution of the original operator differential equation () can be obtained from the definition (2) of x t as x t (ϑ) = x(t + ϑ) = y (t)s (ϑ) + y 2 (t)s 2 (ϑ) + w(t)(ϑ) r(cos(ωt)s (ϑ) ω sin(ωt)s 2 (ϑ)). The periodic solution of the delay-differential equation (4) can be obtained in the form x(t) = x t () y (t)s () + y 2 (t)s 2 () ( ) cos(ωt) = r. (36) ω sin(ωt) Since the relative damping factor ζ is usually far less than in realistic machine tool structures, the first-order Taylor expansion of the amplitude r with respect to ζ is also a good approximation 3 + ζ r 9 p. 5 p cr Let us transform the nondimensonal time and displacement back to the original ones. Selecting the first coordinate of Equation (36), we obtain the approximate form of the unstable periodic motion embedded in the regenerative machine tool vibrations for p<p cr (see also [7]) p cos(ω n + 2ζ t). p cr x(t) ζ 5 f 7. Numerical Results The results of the above sections were confirmed numerically. Simulations with ζ =., j = were carried out (see Equations (9)). The full delay equation (4, 5) was integrated in Mathematica. To find the amplitude of the unstable limit cycle this equation was integrated with

14 34 T. Kalmár-Nagy et al. Figure 4. Bifurcation diagram. sinusoidal initial functions of different amplitudes. The growth or decay of the solution (after some transient) decides whether the solution is outside or inside of the unstable limit cycle. Using a bisection routine allows the computation of the location of the unstable limit cycle with good accuracy. The bifurcation diagram (presenting the amplitude of the unstable limit cycle vs the normalized bifurcation parameter) is shown in Figure 4, together with the analytical approximation (solid line). The agreement is excellent. 8. Conclusions The existence and nature of a Hopf bifurcation in the delay-differential equation for selfexcited tool vibration is presented and proved analytically with the help of the Center Manifold and Hopf Bifurcation Theory. The simple results are due to the special structure of the nonlinearities considered in the cutting force dependence on the chip thickness. On the other hand this analysis is local in the sense that it does not account for nonlinear phenomena as the tool leaves the material. In this case the regenerative effect disappears, and the result of the local analysis is not valid anymore [3, 9]. Finally, the semi-analytical and numerical results of Nayfeh et al. [3] show some cases where a slight supercritical bifurcation appears before the birth of the unstable limit cycle, and they present also some robust supercritical Hopf bifurcations. These results were calculated at critical parameter values somewhat away from the notches of the stability chart chosen in this study. The model considered there also contained structural nonlinearities. Appendix CANONICAL FORM FOR ORDINARY AND DELAY DIFFERENTIAL EQUATIONS In this Appendix we will show an analogy between ordinary and delay differential equations thus motivating the definitions of the differential operator, its adjoint and the bilinear form used to investigate Hopf bifurcation in delay equations. In particular it is shown that the time-delay problem leads to an operator that is the generalization of the defining matrix in a system of ODEs with constant coefficients.

15 CANONICAL FORM FOR ODES Subcritical Hopf Bifurcation in the Delay Equation Model 35 Here we assume that x = is a fixed point (this can always be achieved with a translation) of the system of nonlinear ordinary differential equations ẋ(t) = Ax(t) + f(x(t)) (A.) and the matrix A has a pair of pure imaginary eigenvalues ±iω while all its other eigenvalues are stable (have real part less than zero). The linear part ẋ(t) = Ax(t) of Equation (A.) can be transformed into a form that makes the behavior of the solutions more transparent. This is achieved by using the transformation y(t) = Bx(t). (A.2) Then Equation (A.) can be rewritten in terms of the new coordinates as (the BABy formula) ẏ(t) = BAx(t) + Bf(x(t))= BAB y(t) + Bf(B y(t)) = ω ω y(t) + g(y(t)), } {{ } J (A.3) with containing the Jordan blocks corresponding to the stable eigenvalues. Or with the decompositions y y = y 2, g = w we can write ẏ = ωy 2 + g (y), ẏ 2 = ωy + g 2 (y), ẇ = w + g w (y). g g 2 g w, The geometric meaning of Equation (A.2) is to define the new coordinates as projections of x onto the real and imaginary part of the critical eigenvector of A. This eigenvector satisfies A n = iωn, n = n + in 2. (A.4) The projection is achieved with the help of the usual scalar product (u, v) = u v (where u is the complex conjugate transpose (adjoint) of u) as y i (t) = (n i, x(t)) = n i x(t). (A.5) Then the time evolution of a new coordinate can be expressed as ẏ i = (n i, ẋ(t)) = (s i, Ax(t) + f(x(t))) = (n i, Ax(t)) + (n i, f(x(t))) = (A n i, x(t)) + (n i, f(x(t))) = n i Ax(t) + n i f(x(t)),

16 36 T. Kalmár-Nagy et al. where we used the linearity of the scalar product and the identity (u, Av) = (A u, v). This result is equivalent with Equation (A.3). The coordinates y (t), y 2 (t) of the linear system ẏ(t) = Jy(t) describe stable (but not asymptotically stable) solutions, while the other coordinates represent exponentially decaying ones. In other words the linear equation ẏ(t) = Jy(t) has a two-dimensional attractive invariant subspace (a plane). To obtain the two real vectors that span this plane we first find the two complex conjugate eigenvectors that satisfy Js = iωs, J s = iω s. (A.6) (A.7) These are s = i, s = i. The two real vectors s = Re s =, s 2 = Im s = span the plane in question. n, s satisfy the orthonormality conditions (n, s ) = (n 2, s 2 ) =, (A.8) (n, s 2 ) = (n 2, s ) =. (A.9) Note that since (n, s) = (n, s ) + (n 2, s 2 ) + i((n 2, s ) (n, s 2 )) Equations (A.8) and (A.9) are equivalent to (n, s) = 2. Equations (A.6) and (A.7) can also be written as Js = ωs 2, Js 2 = ωs, which can then be solved for the real vectors.

17 CANONICAL FORM FOR DDES Subcritical Hopf Bifurcation in the Delay Equation Model 37 Let us first consider a linear scalar autonomous delay differential equation (and the corresponding initial function) of the form ẋ(t) = Lx(t) + Rx(t τ)+ f(x(t),x(t τ)), x(t) = φ(t) t [ τ,). (A.) The first goal is to put Equation (A.) into a form similar to Equation (A.). Here an attempted numerical solution could give a clue. Discretizing Equation (A.) leads to dx i dϑ dϑ (x i x i ), i =,...,N, dx i dϑ = Lx + Rx N + f(x,x N ). ϑ= Taking the limit dϑ, and defining the shift of time (a chunk of a function) x t (ϑ) = x(t + ϑ), we have the following d dϑ x t(ϑ) = d dϑ x t(ϑ), ϑ [ τ,), d dϑ x t(ϑ) = Lx t () + Rx t ( τ)+ f(x t (), x t ( τ)). ϑ= This motivates our definition of the linear differential operator A Au(ϑ) = { d dϑ u(ϑ), ϑ [ τ,), Lu() + Ru( τ), ϑ =, (A.) and the nonlinear operator F {, ϑ [ τ,), F (u)(ϑ) = f(u()), ϑ =, (A.2) Since d/dϑ = d/dt, we can rewrite Equation (A.) as d dt x t(ϑ) =ẋ t (ϑ) = Ax t (ϑ) + F (x t )(ϑ). This operator formulation can be extended to multidimensional systems as well ẋ t (ϑ) = Ax t (ϑ) + F (x t )(ϑ). (A.3) This form is very similar to the system of ODEs (A.). There is one very important difference, though. Equation (A.3) represents an infinite-dimensional system. However, the infinitedimensional phase space of its linear part can also be split into stable, unstable and center subspaces corresponding to eigenvalues having positive, negative and zero real part. If we

18 38 T. Kalmár-Nagy et al. focus our attention to the case where the operator has imaginary eigenvalues, it means that A has an pair of complex conjugate eigenfunctions corresponding to ±iω satisfying As(ϑ) = iωis(ϑ), (A.4) A s (ϑ) = iωi s (ϑ), (A.5) where the identity operator I (this seemingly superfluous definition is intended to make our life easier as a bookkeping device) is defined as { u(θ), θ =, Iu(θ) = u(), θ =. Note that Equations (A.4) and (A.5) represent a boundary value problem (because of the definition of A). Introducing the real functions s (ϑ) = Re s(ϑ), s 2 (ϑ) = Im s(ϑ). Equations (A.4) and (A.5) can be rewritten as As (ϑ) = ωis 2 (ϑ), As 2 (ϑ) = ωis (ϑ). The two functions s (ϑ), s 2 (ϑ) span the center subspace which is tangent to the twodimensional center manifold embedded in the infinite-dimensional phase space. With the help of these functions we can try to define the new coordinates (similarly to Equation (A.5)) y (t) = (n (ϑ), x t (ϑ)), y 2 (t) = (n 2 (ϑ), x t (ϑ)). (A.6) where n satisfies A n = iωn. The evolution of the new coordinate y would then be given by ẏ (t) = (n (ϑ), ẋ t (ϑ)) = (n (ϑ), Ax t (ϑ) + F (x t )(ϑ)) = (A n (ϑ), x t (ϑ)) + (n (ϑ), F (x t )(ϑ)). Two questions arise immediately: how shall we define the pairing (.,.) and what is the adjoint operator A? To answer the first question we can first try to use the usual inner product in the space of continously differentiable functions on [ τ,) (u(ϑ), v(ϑ)) = τ u (ϑ)v(ϑ) dϑ. (A.7) However, we also want to include the boundary terms at ϑ = from Equations (A.) and (A.2) so we can try to modify Equation (A.7) as (u(ϑ), vt(ϑ)) = u (ϑ)v(ϑ) dϑ + u ()v(). τ (A.8)

19 Subcritical Hopf Bifurcation in the Delay Equation Model 39 Now we try to find the adjoint operator from the definition (A u, v) = (u, Av) (A u, v) = A uv dϑ +[A u()] v(), (A.9) τ (u, Av) = u Av dϑ + u ()Av() τ by parts d = dϑ u v dϑ + u (ϑ)v(ϑ) τ + u ()[Lv() + Rv( τ)] τ d = dϑ u v dϑ + u ()v() u (ϑ)v(ϑ) τ = τ + u ()Rv( τ)+ u ()Lv() τ ( d ) u vdϑ +[(I + L) u()] v() dϑ u ( τ)v( τ)+ u ()Rv( τ). (A.2) The first two terms of Equation (A.2) are similar to those in Equation (A.9) so we seek to eliminate u ()Rv( τ) u ( τ)v( τ). Since this term is usually nonzero, we can try to modify Equation (A.8) to get u ()Rv( τ) u (τ τ)rv( τ) = instead. This can be achieved with the modification (u(ϑ), v(ϑ)) = u (ϑ + τ)rv(ϑ) dϑ + u ()v(). (A.2) τ Using Equation (A.2) (u, Av) = τ Defining γ = ϑ + τ d dϑ u (ϑ + τ)rv(ϑ) dϑ +[L u() + R u(τ)] v(). (u, Av) = (A u, v) τ ( = d ) u (γ )Rv(γ τ)dγ +[L u() + R u(τ)] v() dγ

20 4 T. Kalmár-Nagy et al. gives the definition of the adjoint operator { d u(γ ), A dγ u(γ ) = γ (,τ], L u() + R u(τ), γ =, with the two complex conjugate eigenfunctions A n(γ ) = iωin(γ ), A n (γ ) = iωi n (γ ). (A.22) (A.23) Introducing the real functions n (γ ) = Re n(γ ), n 2 (γ ) = Im n(γ ). Equations (A.22) and (A.23) can be rewritten as A n (γ ) = ωin 2 (γ ), A n 2 (γ ) = ωin (γ ). Since Equation (A.2) requires functions from two different spaces (C [,] and C [,] )itis a bilinear form instead of an inner product. The orthonormality conditions (see Equations (A.8) and (A.9)) are (n, s ) = (n 2, s 2 ) =, (n 2, s ) = (n, s 2 ) =. The new coordinates y, y 2 can be found by the projections (instead of Equation (A.6)) y (t) = y t () = (n, x t ) ϑ=, y 2 (t) = y 2t () = (n 2, x t ) ϑ=. Now x t (ϑ) can be decomposed as x t (ϑ) = y (t)s (ϑ) + y 2 (t)s 2 (ϑ) + w(t)(ϑ) (A.24) and the operator differential equation (A.3) can be transformed into the canonical form ẏ = (n, ẋ t ) ϑ= = (n, Ax t + F (x t )) ϑ= = (n, Ax t ) ϑ= + (n, F (x t )) ϑ= = (A n, x t ) ϑ= + (n, F (x t )) ϑ= = ω(n 2, x t ) ϑ= + (n, F (x t )) ϑ= = ωy 2 + n T ()F, ẏ 2 = (n 2, ẋ t ) ϑ= = ωy + n T 2 (), F

21 Subcritical Hopf Bifurcation in the Delay Equation Model 4 where F = F (y (t)s () + y 2 (t)s 2 () + w(t)()) was used and ẇ = d dt (x t y s y 2 s 2 ) = Ax t + F (x t ) ẏ Is ẏ 2 Is 2 = A(y s + y 2 s 2 + w) + F (x t ) ẏ Is ẏ 2 Is 2 = y ( ωis 2 ) + y 2 (ωis ) + Aw + F (x t ) (ωy 2 + n T ()F)Is ( ωy + n T 2 ()F)Is 2 = Aw + F (x t ) n T ()FIs n T 2 ()FIs 2 = { d dϑ w nt ()Fs n T 2 ()Fs 2, ϑ [ τ,), Lw() + Rw( τ)+ F n T ()Fs () n T 2 ()Fs 2(), ϑ =. Acknowledgements The authors would like to thank Drs Dave Gilsinn, Jon Pratt, Richard Rand and Steven Yeung for their valuable comments. References. Burns, T. J. and Davies, M. A., Nonlinear dynamics model for chip segmentation in machining, Physical Review Letters 79(3), 997, Campbell, S. A., Bélair, J., Ohira, T., and Milton, J., Complex dynamics and multistability in a damped oscillator with delayed negative feedback, Journal of Dynamics and Differential Equations 7, 995, Doi, S. and Kato, S., Chatter vibration of lathe tools, Transactions of the American Society of Mechanical Engineers 78(5), 956, Fofana, M. S., Delay dynamical systems with applications to machine-tool chatter, Ph.D. Thesis, University of Waterloo, Department of Civil Engineering, Guckenheimer, J. and Holmes, P. J., Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields, Applied Mathematical Sciences, Vol. 42, Springer-Verlag, New York, Hale, J. K., Theory of Functional Differential Equations, Applied Mathematical Sciences, Vol. 3, Springer- Verlag, New York, Hassard, B. D., Kazarinoff, N. D., and Wan, Y. H., Theory and Applications of Hopf Bifurcations, London Mathematical Society Lecture Note Series, Vol. 4, Cambridge University Press, Cambridge. 8. Johnson, M. A., Nonlinear differential equations with delay as models for vibrations in the machining of metals, Ph.D. Thesis, Cornell University, Kalmár-Nagy, T., Pratt, J. R., Davies, M. A., and Kennedy, M. D., Experimental and analytical investigation of the subcritical instability in turning, in Proceedings of the 999 ASME Design Engineering Technical Conferences, ASME, New York, 999, DETC99/VIB8-, pp. 9.. Kalmár-Nagy, T., Stépán, G., and Moon, F. C., Regenerative machine tool vibrations, in Dynamics of Continuous, Discrete and Impulsive Systems, to appear.. Kuang, Y., Delay Differential Equations with Applications in Population Dynamics, Mathematics in Science and Engineering, No. 9, Academic Press, New York, Moon, F. C., Chaotic dynamics and fractals in material removal processes, in Nonlinearity and Chaos in Engineering Dynamics, J. Thompson and S. Bishop (eds.), Wiley, New York, 994, pp Nayfeh, A., Chin, C., and Pratt, J., Applications of perturbation methods to tool chatter dynamics, in Dynamics and Chaos in Manufacturing Processes, F. C. Moon (ed.), Wiley, New York, 997, pp Nayfeh, A. H. and Balachandran, B., Applied Nonlinear Dynamics, Wiley, New York, 995.

22 42 T. Kalmár-Nagy et al. 5. Shi, H. M. and Tobias, S. A., Theory of finite amplitude machine tool instability, International Journal of Machine Tool Design and Research 24(), 984, Stépán, G., Retarded Dynamical Systems: Stability and Characteristic Functions, Pitman Research Notes in Mathematics, Vol. 2, Longman Scientific and Technical, Harlow, Stépán, G., Delay-differential equation models for machine tool chatter, in Dynamics and Chaos in Manufacturing Processes, F. C. Moon (ed.), Wiley, New York, 997, pp Taylor, F. W., On the art of cutting metals, Transactions of the American Society of Mechanical Engineers 28, 97, Tlusty, J. and Spacek, L., Self-Excited Vibrations on Machine Tools, Nakl CSAV, Prague, 954 [in Czech]. 2. Tobias, S. A., Machine Tool Vibration, Blackie and Son, Glasgow, 965.

On the robustness of stable turning processes

On the robustness of stable turning processes 3 Int. J. Machining and Machinability of Materials, Vol. 4, No. 4, 8 On the robustness of stable turning processes Zoltan Dombovari* Department of Applied Mechanics, Budapest University of Technology and

More information

Analytical estimations of limit cycle amplitude for delay-differential equations

Analytical estimations of limit cycle amplitude for delay-differential equations Electronic Journal of Qualitative Theory of Differential Equations 2016, No. 77, 1 10; doi: 10.14232/ejqtde.2016.1.77 http://www.math.u-szeged.hu/ejqtde/ Analytical estimations of limit cycle amplitude

More information

HOPF BIFURCATION CALCULATIONS IN DELAYED SYSTEMS

HOPF BIFURCATION CALCULATIONS IN DELAYED SYSTEMS PERIODICA POLYTECHNICA SER. MECH. ENG. VOL. 48, NO. 2, PP. 89 200 2004 HOPF BIFURCATION CALCULATIONS IN DELAYED SYSTEMS Gábor OROSZ Bristol Centre for Applied Nonlinear Mathematics Department of Engineering

More information

On the analysis of the double Hopf bifurcation in machining processes via center manifold reduction

On the analysis of the double Hopf bifurcation in machining processes via center manifold reduction rspa.royalsocietypublishing.org Research Article submitted to journal On the analysis of the double Hopf bifurcation in machining processes via center manifold reduction T. G. Molnar, Z. Dombovari, T.

More information

Identification Methods for Structural Systems

Identification Methods for Structural Systems Prof. Dr. Eleni Chatzi System Stability Fundamentals Overview System Stability Assume given a dynamic system with input u(t) and output x(t). The stability property of a dynamic system can be defined from

More information

Additive resonances of a controlled van der Pol-Duffing oscillator

Additive resonances of a controlled van der Pol-Duffing oscillator Additive resonances of a controlled van der Pol-Duffing oscillator This paper has been published in Journal of Sound and Vibration vol. 5 issue - 8 pp.-. J.C. Ji N. Zhang Faculty of Engineering University

More information

DETC DELAY DIFFERENTIAL EQUATIONS IN THE DYNAMICS OF GENE COPYING

DETC DELAY DIFFERENTIAL EQUATIONS IN THE DYNAMICS OF GENE COPYING Proceedings of the ASME 2007 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2007 September 4-7, 2007, Las Vegas, Nevada, USA DETC2007-3424

More information

A Model of Evolutionary Dynamics with Quasiperiodic Forcing

A Model of Evolutionary Dynamics with Quasiperiodic Forcing paper presented at Society for Experimental Mechanics (SEM) IMAC XXXIII Conference on Structural Dynamics February 2-5, 205, Orlando FL A Model of Evolutionary Dynamics with Quasiperiodic Forcing Elizabeth

More information

Differential-Delay Equations

Differential-Delay Equations from "Complex Systems: Fractionality, Time-delay and Synchronization" Springer 011 Chapter 3 Differential-Delay Equations Richard Rand Abstract Periodic motions in DDE (Differential-Delay Equations) are

More information

Three ways of treating a linear delay differential equation

Three ways of treating a linear delay differential equation Proceedings of the 5th International Conference on Nonlinear Dynamics ND-KhPI2016 September 27-30, 2016, Kharkov, Ukraine Three ways of treating a linear delay differential equation Si Mohamed Sah 1 *,

More information

1. < 0: the eigenvalues are real and have opposite signs; the fixed point is a saddle point

1. < 0: the eigenvalues are real and have opposite signs; the fixed point is a saddle point Solving a Linear System τ = trace(a) = a + d = λ 1 + λ 2 λ 1,2 = τ± = det(a) = ad bc = λ 1 λ 2 Classification of Fixed Points τ 2 4 1. < 0: the eigenvalues are real and have opposite signs; the fixed point

More information

Stability and bifurcation of a simple neural network with multiple time delays.

Stability and bifurcation of a simple neural network with multiple time delays. Fields Institute Communications Volume, 999 Stability and bifurcation of a simple neural network with multiple time delays. Sue Ann Campbell Department of Applied Mathematics University of Waterloo Waterloo

More information

Available online at ScienceDirect. Procedia IUTAM 19 (2016 ) IUTAM Symposium Analytical Methods in Nonlinear Dynamics

Available online at   ScienceDirect. Procedia IUTAM 19 (2016 ) IUTAM Symposium Analytical Methods in Nonlinear Dynamics Available online at www.sciencedirect.com ScienceDirect Procedia IUTAM 19 (2016 ) 11 18 IUTAM Symposium Analytical Methods in Nonlinear Dynamics A model of evolutionary dynamics with quasiperiodic forcing

More information

The Higgins-Selkov oscillator

The Higgins-Selkov oscillator The Higgins-Selkov oscillator May 14, 2014 Here I analyse the long-time behaviour of the Higgins-Selkov oscillator. The system is ẋ = k 0 k 1 xy 2, (1 ẏ = k 1 xy 2 k 2 y. (2 The unknowns x and y, being

More information

STABILITY. Phase portraits and local stability

STABILITY. Phase portraits and local stability MAS271 Methods for differential equations Dr. R. Jain STABILITY Phase portraits and local stability We are interested in system of ordinary differential equations of the form ẋ = f(x, y), ẏ = g(x, y),

More information

STABILITY ANALYSIS OF DAMPED SDOF SYSTEMS WITH TWO TIME DELAYS IN STATE FEEDBACK

STABILITY ANALYSIS OF DAMPED SDOF SYSTEMS WITH TWO TIME DELAYS IN STATE FEEDBACK Journal of Sound and Vibration (1998) 214(2), 213 225 Article No. sv971499 STABILITY ANALYSIS OF DAMPED SDOF SYSTEMS WITH TWO TIME DELAYS IN STATE FEEDBACK H. Y. HU ANDZ. H. WANG Institute of Vibration

More information

Difference Resonances in a controlled van der Pol-Duffing oscillator involving time. delay

Difference Resonances in a controlled van der Pol-Duffing oscillator involving time. delay Difference Resonances in a controlled van der Pol-Duffing oscillator involving time delay This paper was published in the journal Chaos, Solitions & Fractals, vol.4, no., pp.975-98, Oct 9 J.C. Ji, N. Zhang,

More information

Dynamics of Two Coupled van der Pol Oscillators with Delay Coupling Revisited

Dynamics of Two Coupled van der Pol Oscillators with Delay Coupling Revisited Dynamics of Two Coupled van der Pol Oscillators with Delay Coupling Revisited arxiv:1705.03100v1 [math.ds] 8 May 017 Mark Gluzman Center for Applied Mathematics Cornell University and Richard Rand Dept.

More information

Differential Equations 2280 Sample Midterm Exam 3 with Solutions Exam Date: 24 April 2015 at 12:50pm

Differential Equations 2280 Sample Midterm Exam 3 with Solutions Exam Date: 24 April 2015 at 12:50pm Differential Equations 228 Sample Midterm Exam 3 with Solutions Exam Date: 24 April 25 at 2:5pm Instructions: This in-class exam is 5 minutes. No calculators, notes, tables or books. No answer check is

More information

Chapter 14 Three Ways of Treating a Linear Delay Differential Equation

Chapter 14 Three Ways of Treating a Linear Delay Differential Equation Chapter 14 Three Ways of Treating a Linear Delay Differential Equation Si Mohamed Sah and Richard H. Rand Abstract This work concerns the occurrence of Hopf bifurcations in delay differential equations

More information

ELEC 3035, Lecture 3: Autonomous systems Ivan Markovsky

ELEC 3035, Lecture 3: Autonomous systems Ivan Markovsky ELEC 3035, Lecture 3: Autonomous systems Ivan Markovsky Equilibrium points and linearization Eigenvalue decomposition and modal form State transition matrix and matrix exponential Stability ELEC 3035 (Part

More information

Oscillation Control in Delayed Feedback Systems

Oscillation Control in Delayed Feedback Systems Oscillation Control in Delayed Feedback Systems Fatihcan M. Atay (atay@member.ams.org) Preprint. Final version in Lecture Notes in Control and Information Sciences Vol. 273, pp. 3 6 (22) Abstract. The

More information

Analysis of the Chatter Instability in a Nonlinear Model for Drilling

Analysis of the Chatter Instability in a Nonlinear Model for Drilling Sue Ann Campbell Department of Applied Mathematics, University of Waterloo, Waterloo, ON N2L 3G1 Canada e-mail: sacampbell@uwaterloo.ca Emily Stone Department of Mathematical Sciences, The University of

More information

Phase Synchronization

Phase Synchronization Phase Synchronization Lecture by: Zhibin Guo Notes by: Xiang Fan May 10, 2016 1 Introduction For any mode or fluctuation, we always have where S(x, t) is phase. If a mode amplitude satisfies ϕ k = ϕ k

More information

Journal of Applied Nonlinear Dynamics

Journal of Applied Nonlinear Dynamics Journal of Applied Nonlinear Dynamics 4(2) (2015) 131 140 Journal of Applied Nonlinear Dynamics https://lhscientificpublishing.com/journals/jand-default.aspx A Model of Evolutionary Dynamics with Quasiperiodic

More information

Identification Methods for Structural Systems. Prof. Dr. Eleni Chatzi Lecture March, 2016

Identification Methods for Structural Systems. Prof. Dr. Eleni Chatzi Lecture March, 2016 Prof. Dr. Eleni Chatzi Lecture 4-09. March, 2016 Fundamentals Overview Multiple DOF Systems State-space Formulation Eigenvalue Analysis The Mode Superposition Method The effect of Damping on Structural

More information

Approximation of Top Lyapunov Exponent of Stochastic Delayed Turning Model Using Fokker-Planck Approach

Approximation of Top Lyapunov Exponent of Stochastic Delayed Turning Model Using Fokker-Planck Approach Approximation of Top Lyapunov Exponent of Stochastic Delayed Turning Model Using Fokker-Planck Approach Henrik T. Sykora, Walter V. Wedig, Daniel Bachrathy and Gabor Stepan Department of Applied Mechanics,

More information

One Dimensional Dynamical Systems

One Dimensional Dynamical Systems 16 CHAPTER 2 One Dimensional Dynamical Systems We begin by analyzing some dynamical systems with one-dimensional phase spaces, and in particular their bifurcations. All equations in this Chapter are scalar

More information

Vibrations: Second Order Systems with One Degree of Freedom, Free Response

Vibrations: Second Order Systems with One Degree of Freedom, Free Response Single Degree of Freedom System 1.003J/1.053J Dynamics and Control I, Spring 007 Professor Thomas Peacock 5//007 Lecture 0 Vibrations: Second Order Systems with One Degree of Freedom, Free Response Single

More information

Exercises Lecture 15

Exercises Lecture 15 AM1 Mathematical Analysis 1 Oct. 011 Feb. 01 Date: January 7 Exercises Lecture 15 Harmonic Oscillators In classical mechanics, a harmonic oscillator is a system that, when displaced from its equilibrium

More information

HOPF BIFURCATION CONTROL WITH PD CONTROLLER

HOPF BIFURCATION CONTROL WITH PD CONTROLLER HOPF BIFURCATION CONTROL WITH PD CONTROLLER M. DARVISHI AND H.M. MOHAMMADINEJAD DEPARTMENT OF MATHEMATICS, FACULTY OF MATHEMATICS AND STATISTICS, UNIVERSITY OF BIRJAND, BIRJAND, IRAN E-MAILS: M.DARVISHI@BIRJAND.AC.IR,

More information

Introduction to Modern Control MT 2016

Introduction to Modern Control MT 2016 CDT Autonomous and Intelligent Machines & Systems Introduction to Modern Control MT 2016 Alessandro Abate Lecture 2 First-order ordinary differential equations (ODE) Solution of a linear ODE Hints to nonlinear

More information

The Phasor Analysis Method For Harmonically Forced Linear Systems

The Phasor Analysis Method For Harmonically Forced Linear Systems The Phasor Analysis Method For Harmonically Forced Linear Systems Daniel S. Stutts, Ph.D. April 4, 1999 Revised: 10-15-010, 9-1-011 1 Introduction One of the most common tasks in vibration analysis is

More information

Identification Methods for Structural Systems. Prof. Dr. Eleni Chatzi System Stability - 26 March, 2014

Identification Methods for Structural Systems. Prof. Dr. Eleni Chatzi System Stability - 26 March, 2014 Prof. Dr. Eleni Chatzi System Stability - 26 March, 24 Fundamentals Overview System Stability Assume given a dynamic system with input u(t) and output x(t). The stability property of a dynamic system can

More information

B5.6 Nonlinear Systems

B5.6 Nonlinear Systems B5.6 Nonlinear Systems 5. Global Bifurcations, Homoclinic chaos, Melnikov s method Alain Goriely 2018 Mathematical Institute, University of Oxford Table of contents 1. Motivation 1.1 The problem 1.2 A

More information

2:1 Resonance in the delayed nonlinear Mathieu equation

2:1 Resonance in the delayed nonlinear Mathieu equation Nonlinear Dyn 007) 50:31 35 DOI 10.1007/s11071-006-916-5 ORIGINAL ARTICLE :1 Resonance in the delayed nonlinear Mathieu equation Tina M. Morrison Richard H. Rand Received: 9 March 006 / Accepted: 19 September

More information

Collocation approximation of the monodromy operator of periodic, linear DDEs

Collocation approximation of the monodromy operator of periodic, linear DDEs p. Collocation approximation of the monodromy operator of periodic, linear DDEs Ed Bueler 1, Victoria Averina 2, and Eric Butcher 3 13 July, 2004 SIAM Annual Meeting 2004, Portland 1=Dept. of Math. Sci.,

More information

2:2:1 Resonance in the Quasiperiodic Mathieu Equation

2:2:1 Resonance in the Quasiperiodic Mathieu Equation Nonlinear Dynamics 31: 367 374, 003. 003 Kluwer Academic Publishers. Printed in the Netherlands. ::1 Resonance in the Quasiperiodic Mathieu Equation RICHARD RAND Department of Theoretical and Applied Mechanics,

More information

University of Bristol - Explore Bristol Research. Early version, also known as pre-print

University of Bristol - Explore Bristol Research. Early version, also known as pre-print Orosz, G., & Stepan, G. (4). Hopf bifurcation calculations in delayed systems with translational symmetry. https://doi.org/1.17/s33-4- 65-4 Early version, also known as pre-print Link to published version

More information

Stability of Feedback Solutions for Infinite Horizon Noncooperative Differential Games

Stability of Feedback Solutions for Infinite Horizon Noncooperative Differential Games Stability of Feedback Solutions for Infinite Horizon Noncooperative Differential Games Alberto Bressan ) and Khai T. Nguyen ) *) Department of Mathematics, Penn State University **) Department of Mathematics,

More information

Hopf Bifurcation in a Scalar Reaction Diffusion Equation

Hopf Bifurcation in a Scalar Reaction Diffusion Equation journal of differential equations 140, 209222 (1997) article no. DE973307 Hopf Bifurcation in a Scalar Reaction Diffusion Equation Patrick Guidotti and Sandro Merino Mathematisches Institut, Universita

More information

CALCULATION OF NONLINEAR VIBRATIONS OF PIECEWISE-LINEAR SYSTEMS USING THE SHOOTING METHOD

CALCULATION OF NONLINEAR VIBRATIONS OF PIECEWISE-LINEAR SYSTEMS USING THE SHOOTING METHOD Vietnam Journal of Mechanics, VAST, Vol. 34, No. 3 (2012), pp. 157 167 CALCULATION OF NONLINEAR VIBRATIONS OF PIECEWISE-LINEAR SYSTEMS USING THE SHOOTING METHOD Nguyen Van Khang, Hoang Manh Cuong, Nguyen

More information

Complex Dynamic Systems: Qualitative vs Quantitative analysis

Complex Dynamic Systems: Qualitative vs Quantitative analysis Complex Dynamic Systems: Qualitative vs Quantitative analysis Complex Dynamic Systems Chiara Mocenni Department of Information Engineering and Mathematics University of Siena (mocenni@diism.unisi.it) Dynamic

More information

Linearization of Differential Equation Models

Linearization of Differential Equation Models Linearization of Differential Equation Models 1 Motivation We cannot solve most nonlinear models, so we often instead try to get an overall feel for the way the model behaves: we sometimes talk about looking

More information

Complicated behavior of dynamical systems. Mathematical methods and computer experiments.

Complicated behavior of dynamical systems. Mathematical methods and computer experiments. Complicated behavior of dynamical systems. Mathematical methods and computer experiments. Kuznetsov N.V. 1, Leonov G.A. 1, and Seledzhi S.M. 1 St.Petersburg State University Universitetsky pr. 28 198504

More information

Damped harmonic motion

Damped harmonic motion Damped harmonic motion March 3, 016 Harmonic motion is studied in the presence of a damping force proportional to the velocity. The complex method is introduced, and the different cases of under-damping,

More information

DynamicsofTwoCoupledVanderPolOscillatorswithDelayCouplingRevisited

DynamicsofTwoCoupledVanderPolOscillatorswithDelayCouplingRevisited Global Journal of Science Frontier Research: F Mathematics and Decision Sciences Volume 7 Issue 5 Version.0 Year 07 Type : Double Blind Peer Reviewed International Research Journal Publisher: Global Journals

More information

(8.51) ẋ = A(λ)x + F(x, λ), where λ lr, the matrix A(λ) and function F(x, λ) are C k -functions with k 1,

(8.51) ẋ = A(λ)x + F(x, λ), where λ lr, the matrix A(λ) and function F(x, λ) are C k -functions with k 1, 2.8.7. Poincaré-Andronov-Hopf Bifurcation. In the previous section, we have given a rather detailed method for determining the periodic orbits of a two dimensional system which is the perturbation of a

More information

5.2.2 Planar Andronov-Hopf bifurcation

5.2.2 Planar Andronov-Hopf bifurcation 138 CHAPTER 5. LOCAL BIFURCATION THEORY 5.. Planar Andronov-Hopf bifurcation What happens if a planar system has an equilibrium x = x 0 at some parameter value α = α 0 with eigenvalues λ 1, = ±iω 0, ω

More information

Lecture 5. Numerical continuation of connecting orbits of iterated maps and ODEs. Yu.A. Kuznetsov (Utrecht University, NL)

Lecture 5. Numerical continuation of connecting orbits of iterated maps and ODEs. Yu.A. Kuznetsov (Utrecht University, NL) Lecture 5 Numerical continuation of connecting orbits of iterated maps and ODEs Yu.A. Kuznetsov (Utrecht University, NL) May 26, 2009 1 Contents 1. Point-to-point connections. 2. Continuation of homoclinic

More information

1. Find the solution of the following uncontrolled linear system. 2 α 1 1

1. Find the solution of the following uncontrolled linear system. 2 α 1 1 Appendix B Revision Problems 1. Find the solution of the following uncontrolled linear system 0 1 1 ẋ = x, x(0) =. 2 3 1 Class test, August 1998 2. Given the linear system described by 2 α 1 1 ẋ = x +

More information

NBA Lecture 1. Simplest bifurcations in n-dimensional ODEs. Yu.A. Kuznetsov (Utrecht University, NL) March 14, 2011

NBA Lecture 1. Simplest bifurcations in n-dimensional ODEs. Yu.A. Kuznetsov (Utrecht University, NL) March 14, 2011 NBA Lecture 1 Simplest bifurcations in n-dimensional ODEs Yu.A. Kuznetsov (Utrecht University, NL) March 14, 2011 Contents 1. Solutions and orbits: equilibria cycles connecting orbits other invariant sets

More information

Propagation of longitudinal waves in a random binary rod

Propagation of longitudinal waves in a random binary rod Downloaded By: [University of North Carolina, Charlotte At: 7:3 2 May 28 Waves in Random and Complex Media Vol. 6, No. 4, November 26, 49 46 Propagation of longitudinal waves in a random binary rod YURI

More information

Advanced Vibrations. Elements of Analytical Dynamics. By: H. Ahmadian Lecture One

Advanced Vibrations. Elements of Analytical Dynamics. By: H. Ahmadian Lecture One Advanced Vibrations Lecture One Elements of Analytical Dynamics By: H. Ahmadian ahmadian@iust.ac.ir Elements of Analytical Dynamics Newton's laws were formulated for a single particle Can be extended to

More information

Entrance Exam, Differential Equations April, (Solve exactly 6 out of the 8 problems) y + 2y + y cos(x 2 y) = 0, y(0) = 2, y (0) = 4.

Entrance Exam, Differential Equations April, (Solve exactly 6 out of the 8 problems) y + 2y + y cos(x 2 y) = 0, y(0) = 2, y (0) = 4. Entrance Exam, Differential Equations April, 7 (Solve exactly 6 out of the 8 problems). Consider the following initial value problem: { y + y + y cos(x y) =, y() = y. Find all the values y such that the

More information

AA242B: MECHANICAL VIBRATIONS

AA242B: MECHANICAL VIBRATIONS AA242B: MECHANICAL VIBRATIONS 1 / 50 AA242B: MECHANICAL VIBRATIONS Undamped Vibrations of n-dof Systems These slides are based on the recommended textbook: M. Géradin and D. Rixen, Mechanical Vibrations:

More information

Some solutions of the written exam of January 27th, 2014

Some solutions of the written exam of January 27th, 2014 TEORIA DEI SISTEMI Systems Theory) Prof. C. Manes, Prof. A. Germani Some solutions of the written exam of January 7th, 0 Problem. Consider a feedback control system with unit feedback gain, with the following

More information

Control Systems I. Lecture 4: Diagonalization, Modal Analysis, Intro to Feedback. Readings: Emilio Frazzoli

Control Systems I. Lecture 4: Diagonalization, Modal Analysis, Intro to Feedback. Readings: Emilio Frazzoli Control Systems I Lecture 4: Diagonalization, Modal Analysis, Intro to Feedback Readings: Emilio Frazzoli Institute for Dynamic Systems and Control D-MAVT ETH Zürich October 13, 2017 E. Frazzoli (ETH)

More information

TWO DIMENSIONAL FLOWS. Lecture 5: Limit Cycles and Bifurcations

TWO DIMENSIONAL FLOWS. Lecture 5: Limit Cycles and Bifurcations TWO DIMENSIONAL FLOWS Lecture 5: Limit Cycles and Bifurcations 5. Limit cycles A limit cycle is an isolated closed trajectory [ isolated means that neighbouring trajectories are not closed] Fig. 5.1.1

More information

Hopf Bifurcation Analysis of a Dynamical Heart Model with Time Delay

Hopf Bifurcation Analysis of a Dynamical Heart Model with Time Delay Applied Mathematical Sciences, Vol 11, 2017, no 22, 1089-1095 HIKARI Ltd, wwwm-hikaricom https://doiorg/1012988/ams20177271 Hopf Bifurcation Analysis of a Dynamical Heart Model with Time Delay Luca Guerrini

More information

Autonomous system = system without inputs

Autonomous system = system without inputs Autonomous system = system without inputs State space representation B(A,C) = {y there is x, such that σx = Ax, y = Cx } x is the state, n := dim(x) is the state dimension, y is the output Polynomial representation

More information

2 Discrete growth models, logistic map (Murray, Chapter 2)

2 Discrete growth models, logistic map (Murray, Chapter 2) 2 Discrete growth models, logistic map (Murray, Chapter 2) As argued in Lecture 1 the population of non-overlapping generations can be modelled as a discrete dynamical system. This is an example of an

More information

7 Planar systems of linear ODE

7 Planar systems of linear ODE 7 Planar systems of linear ODE Here I restrict my attention to a very special class of autonomous ODE: linear ODE with constant coefficients This is arguably the only class of ODE for which explicit solution

More information

A Brief Outline of Math 355

A Brief Outline of Math 355 A Brief Outline of Math 355 Lecture 1 The geometry of linear equations; elimination with matrices A system of m linear equations with n unknowns can be thought of geometrically as m hyperplanes intersecting

More information

Dynamics of a mass-spring-pendulum system with vastly different frequencies

Dynamics of a mass-spring-pendulum system with vastly different frequencies Dynamics of a mass-spring-pendulum system with vastly different frequencies Hiba Sheheitli, hs497@cornell.edu Richard H. Rand, rhr2@cornell.edu Cornell University, Ithaca, NY, USA Abstract. We investigate

More information

ODE Homework 1. Due Wed. 19 August 2009; At the beginning of the class

ODE Homework 1. Due Wed. 19 August 2009; At the beginning of the class ODE Homework Due Wed. 9 August 2009; At the beginning of the class. (a) Solve Lẏ + Ry = E sin(ωt) with y(0) = k () L, R, E, ω are positive constants. (b) What is the limit of the solution as ω 0? (c) Is

More information

CMPT 889: Lecture 2 Sinusoids, Complex Exponentials, Spectrum Representation

CMPT 889: Lecture 2 Sinusoids, Complex Exponentials, Spectrum Representation CMPT 889: Lecture 2 Sinusoids, Complex Exponentials, Spectrum Representation Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University September 26, 2005 1 Sinusoids Sinusoids

More information

MATH 205C: STATIONARY PHASE LEMMA

MATH 205C: STATIONARY PHASE LEMMA MATH 205C: STATIONARY PHASE LEMMA For ω, consider an integral of the form I(ω) = e iωf(x) u(x) dx, where u Cc (R n ) complex valued, with support in a compact set K, and f C (R n ) real valued. Thus, I(ω)

More information

8.1 Bifurcations of Equilibria

8.1 Bifurcations of Equilibria 1 81 Bifurcations of Equilibria Bifurcation theory studies qualitative changes in solutions as a parameter varies In general one could study the bifurcation theory of ODEs PDEs integro-differential equations

More information

Stability of flow past a confined cylinder

Stability of flow past a confined cylinder Stability of flow past a confined cylinder Andrew Cliffe and Simon Tavener University of Nottingham and Colorado State University Stability of flow past a confined cylinder p. 1/60 Flow past a cylinder

More information

CHAPTER 6 HOPF-BIFURCATION IN A TWO DIMENSIONAL NONLINEAR DIFFERENTIAL EQUATION

CHAPTER 6 HOPF-BIFURCATION IN A TWO DIMENSIONAL NONLINEAR DIFFERENTIAL EQUATION CHAPTER 6 HOPF-BIFURCATION IN A TWO DIMENSIONAL NONLINEAR DIFFERENTIAL EQUATION [Discussion on this chapter is based on our paper entitled Hopf-Bifurcation Ina Two Dimensional Nonlinear Differential Equation,

More information

BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs

BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs Yuri A. Kuznetsov August, 2010 Contents 1. Solutions and orbits. 2. Equilibria. 3. Periodic orbits and limit cycles. 4. Homoclinic orbits.

More information

PERIOD-N BIFURCATIONS IN MILLING: NUMERICAL AND EXPERIMENTAL VERIFICATION

PERIOD-N BIFURCATIONS IN MILLING: NUMERICAL AND EXPERIMENTAL VERIFICATION PERIOD-N BIFURCATIONS IN MILLING: NUMERICAL AND EXPERIMENTAL VERIFICATION Andrew Honeycutt and Tony L. Schmitz Department of Mechanical Engineering and Engineering Science University of North Carolina

More information

L = 1 2 a(q) q2 V (q).

L = 1 2 a(q) q2 V (q). Physics 3550, Fall 2011 Motion near equilibrium - Small Oscillations Relevant Sections in Text: 5.1 5.6 Motion near equilibrium 1 degree of freedom One of the most important situations in physics is motion

More information

2 Lecture 2: Amplitude equations and Hopf bifurcations

2 Lecture 2: Amplitude equations and Hopf bifurcations Lecture : Amplitude equations and Hopf bifurcations This lecture completes the brief discussion of steady-state bifurcations by discussing vector fields that describe the dynamics near a bifurcation. From

More information

arxiv: v3 [math.ds] 12 Jun 2013

arxiv: v3 [math.ds] 12 Jun 2013 Isostables, isochrons, and Koopman spectrum for the action-angle representation of stable fixed point dynamics A. Mauroy, I. Mezic, and J. Moehlis Department of Mechanical Engineering, University of California

More information

as Hopf Bifurcations in Time-Delay Systems with Band-limited Feedback

as Hopf Bifurcations in Time-Delay Systems with Band-limited Feedback as Hopf Bifurcations in Time-Delay Systems with Band-limited Feedback Lucas Illing and Daniel J. Gauthier Department of Physics Center for Nonlinear and Complex Systems Duke University, North Carolina

More information

Math Ordinary Differential Equations

Math Ordinary Differential Equations Math 411 - Ordinary Differential Equations Review Notes - 1 1 - Basic Theory A first order ordinary differential equation has the form x = f(t, x) (11) Here x = dx/dt Given an initial data x(t 0 ) = x

More information

UNIVERSIDADE DE SÃO PAULO

UNIVERSIDADE DE SÃO PAULO UNIVERSIDADE DE SÃO PAULO Instituto de Ciências Matemáticas e de Computação ISSN 0103-2577 GLOBAL DYNAMICAL ASPECTS OF A GENERALIZED CHEN-WANG DIFFERENTIAL SYSTEM REGILENE D. S. OLIVEIRA CLAUDIA VALLS

More information

Linear and Nonlinear Oscillators (Lecture 2)

Linear and Nonlinear Oscillators (Lecture 2) Linear and Nonlinear Oscillators (Lecture 2) January 25, 2016 7/441 Lecture outline A simple model of a linear oscillator lies in the foundation of many physical phenomena in accelerator dynamics. A typical

More information

Journal of Applied Nonlinear Dynamics

Journal of Applied Nonlinear Dynamics Journal of Applied Nonlinear Dynamics 1(2) (2012) 159 171 Journal of Applied Nonlinear Dynamics https://lhscientificpublishing.com/journals/jand-default.aspx Asymptotic Analysis of the Hopf-Hopf Bifurcation

More information

Elements of linear algebra

Elements of linear algebra Elements of linear algebra Elements of linear algebra A vector space S is a set (numbers, vectors, functions) which has addition and scalar multiplication defined, so that the linear combination c 1 v

More information

Sinusoids. Amplitude and Magnitude. Phase and Period. CMPT 889: Lecture 2 Sinusoids, Complex Exponentials, Spectrum Representation

Sinusoids. Amplitude and Magnitude. Phase and Period. CMPT 889: Lecture 2 Sinusoids, Complex Exponentials, Spectrum Representation Sinusoids CMPT 889: Lecture Sinusoids, Complex Exponentials, Spectrum Representation Tamara Smyth, tamaras@cs.sfu.ca School of Computing Science, Simon Fraser University September 6, 005 Sinusoids are

More information

Chaotic motion. Phys 420/580 Lecture 10

Chaotic motion. Phys 420/580 Lecture 10 Chaotic motion Phys 420/580 Lecture 10 Finite-difference equations Finite difference equation approximates a differential equation as an iterative map (x n+1,v n+1 )=M[(x n,v n )] Evolution from time t

More information

Remark on Hopf Bifurcation Theorem

Remark on Hopf Bifurcation Theorem Remark on Hopf Bifurcation Theorem Krasnosel skii A.M., Rachinskii D.I. Institute for Information Transmission Problems Russian Academy of Sciences 19 Bolshoi Karetny lane, 101447 Moscow, Russia E-mails:

More information

CHALMERS, GÖTEBORGS UNIVERSITET. EXAM for DYNAMICAL SYSTEMS. COURSE CODES: TIF 155, FIM770GU, PhD

CHALMERS, GÖTEBORGS UNIVERSITET. EXAM for DYNAMICAL SYSTEMS. COURSE CODES: TIF 155, FIM770GU, PhD CHALMERS, GÖTEBORGS UNIVERSITET EXAM for DYNAMICAL SYSTEMS COURSE CODES: TIF 155, FIM770GU, PhD Time: Place: Teachers: Allowed material: Not allowed: August 22, 2018, at 08 30 12 30 Johanneberg Jan Meibohm,

More information

Strange dynamics of bilinear oscillator close to grazing

Strange dynamics of bilinear oscillator close to grazing Strange dynamics of bilinear oscillator close to grazing Ekaterina Pavlovskaia, James Ing, Soumitro Banerjee and Marian Wiercigroch Centre for Applied Dynamics Research, School of Engineering, King s College,

More information

Vectors To begin, let us describe an element of the state space as a point with numerical coordinates, that is x 1. x 2. x =

Vectors To begin, let us describe an element of the state space as a point with numerical coordinates, that is x 1. x 2. x = Linear Algebra Review Vectors To begin, let us describe an element of the state space as a point with numerical coordinates, that is x 1 x x = 2. x n Vectors of up to three dimensions are easy to diagram.

More information

Linear Algebra: Matrix Eigenvalue Problems

Linear Algebra: Matrix Eigenvalue Problems CHAPTER8 Linear Algebra: Matrix Eigenvalue Problems Chapter 8 p1 A matrix eigenvalue problem considers the vector equation (1) Ax = λx. 8.0 Linear Algebra: Matrix Eigenvalue Problems Here A is a given

More information

Invariant Manifolds of Dynamical Systems and an application to Space Exploration

Invariant Manifolds of Dynamical Systems and an application to Space Exploration Invariant Manifolds of Dynamical Systems and an application to Space Exploration Mateo Wirth January 13, 2014 1 Abstract In this paper we go over the basics of stable and unstable manifolds associated

More information

Linear Algebra. Min Yan

Linear Algebra. Min Yan Linear Algebra Min Yan January 2, 2018 2 Contents 1 Vector Space 7 1.1 Definition................................. 7 1.1.1 Axioms of Vector Space..................... 7 1.1.2 Consequence of Axiom......................

More information

Symmetry Properties of Confined Convective States

Symmetry Properties of Confined Convective States Symmetry Properties of Confined Convective States John Guckenheimer Cornell University 1 Introduction This paper is a commentary on the experimental observation observations of Bensimon et al. [1] of convection

More information

Hilbert s 16. problem

Hilbert s 16. problem Hilbert s 16. problem Aarhus University Aarhus 24 th March, 2017 Hilbert s Problem Does there exist (minimal) natural numbers H n, for n = 2, 3,..., such that any planar autonomous system of ODE s dx dt

More information

The Effects of Machine Components on Bifurcation and Chaos as Applied to Multimachine System

The Effects of Machine Components on Bifurcation and Chaos as Applied to Multimachine System 1 The Effects of Machine Components on Bifurcation and Chaos as Applied to Multimachine System M. M. Alomari and B. S. Rodanski University of Technology, Sydney (UTS) P.O. Box 123, Broadway NSW 2007, Australia

More information

Lectures on Dynamical Systems. Anatoly Neishtadt

Lectures on Dynamical Systems. Anatoly Neishtadt Lectures on Dynamical Systems Anatoly Neishtadt Lectures for Mathematics Access Grid Instruction and Collaboration (MAGIC) consortium, Loughborough University, 2007 Part 3 LECTURE 14 NORMAL FORMS Resonances

More information

Boulder School for Condensed Matter and Materials Physics. Laurette Tuckerman PMMH-ESPCI-CNRS

Boulder School for Condensed Matter and Materials Physics. Laurette Tuckerman PMMH-ESPCI-CNRS Boulder School for Condensed Matter and Materials Physics Laurette Tuckerman PMMH-ESPCI-CNRS laurette@pmmh.espci.fr Dynamical Systems: A Basic Primer 1 1 Basic bifurcations 1.1 Fixed points and linear

More information

A plane autonomous system is a pair of simultaneous first-order differential equations,

A plane autonomous system is a pair of simultaneous first-order differential equations, Chapter 11 Phase-Plane Techniques 11.1 Plane Autonomous Systems A plane autonomous system is a pair of simultaneous first-order differential equations, ẋ = f(x, y), ẏ = g(x, y). This system has an equilibrium

More information

Stability of an abstract wave equation with delay and a Kelvin Voigt damping

Stability of an abstract wave equation with delay and a Kelvin Voigt damping Stability of an abstract wave equation with delay and a Kelvin Voigt damping University of Monastir/UPSAY/LMV-UVSQ Joint work with Serge Nicaise and Cristina Pignotti Outline 1 Problem The idea Stability

More information

Dynamical Systems with Varying Time Delay in Engineering Applications

Dynamical Systems with Varying Time Delay in Engineering Applications Budapest University of Technology and Economics Department of Applied Mechanics Dynamical Systems with Varying Time Delay in Engineering Applications PhD dissertation Tamás G. Molnár Supervisor: Tamás

More information

Table of contents. d 2 y dx 2, As the equation is linear, these quantities can only be involved in the following manner:

Table of contents. d 2 y dx 2, As the equation is linear, these quantities can only be involved in the following manner: M ath 0 1 E S 1 W inter 0 1 0 Last Updated: January, 01 0 Solving Second Order Linear ODEs Disclaimer: This lecture note tries to provide an alternative approach to the material in Sections 4. 4. 7 and

More information