Chapter 12 - Solved Problems

Similar documents
1. Z-transform: Initial value theorem for causal signal. = u(0) + u(1)z 1 + u(2)z 2 +

1. Partial Fraction Expansion All the polynomials in this note are assumed to be complex polynomials.

Digital Control Systems

Models for Sampled Data Systems

Solution of ODEs using Laplace Transforms. Process Dynamics and Control

Need for transformation?

Chapter 13 Digital Control

Recursive, Infinite Impulse Response (IIR) Digital Filters:

Exercises involving elementary functions

Laplace Transforms Chapter 3

L bor y nnd Union One nnd Inseparable. LOW I'LL, MICHIGAN. WLDNHSDA Y. JULY ), I8T. liuwkll NATIdiNAI, liank

Mathematics 350: Problems to Study Solutions

and A L T O S O L O LOWELL, MICHIGAN, THURSDAY, OCTCBER Mrs. Thomas' Young Men Good Bye 66 Long Illness Have Sport in

Automatic Control Systems theory overview (discrete time systems)

Complex Variables...Review Problems (Residue Calculus Comments)...Fall Initial Draft

CBE507 LECTURE III Controller Design Using State-space Methods. Professor Dae Ryook Yang

Exercises involving elementary functions

Ch. 7: Z-transform Reading

. Then g is holomorphic and bounded in U. So z 0 is a removable singularity of g. Since f(z) = w 0 + 1

The z-transform Part 2

Chapter 7 - Solved Problems

GATE EE Topic wise Questions SIGNALS & SYSTEMS

Theorem [Mean Value Theorem for Harmonic Functions] Let u be harmonic on D(z 0, R). Then for any r (0, R), u(z 0 ) = 1 z z 0 r

Lecture 9: Time-Domain Analysis of Discrete-Time Systems Dr.-Ing. Sudchai Boonto

On rational approximation of algebraic functions. Julius Borcea. Rikard Bøgvad & Boris Shapiro

Control System Design

EE 3054: Signals, Systems, and Transforms Spring A causal discrete-time LTI system is described by the equation. y(n) = 1 4.

Methods for analysis and control of. Lecture 6: Introduction to digital control

Chapter 2 z-transform. X(z) = Z[x(t)] = Z[x(kT)] = Z[x(k)] x(kt)z k = x(kt)z k = x(k)z k. X(z)z k 1 dz 2πj c = 1

EE451/551: Digital Control. Final Exam Review Fall 2013

The Z-Transform. Fall 2012, EE123 Digital Signal Processing. Eigen Functions of LTI System. Eigen Functions of LTI System

MATH 452. SAMPLE 3 SOLUTIONS May 3, (10 pts) Let f(x + iy) = u(x, y) + iv(x, y) be an analytic function. Show that u(x, y) is harmonic.

SAMPLE SOLUTION TO EXAM in MAS501 Control Systems 2 Autumn 2015

Control System Design

EE480.3 Digital Control Systems. Part 7. Controller Design I. - Pole Assignment Method - State Estimation

It is common to think and write in time domain. creating the mathematical description of the. Continuous systems- using Laplace or s-

r/lt.i Ml s." ifcr ' W ATI II. The fnncrnl.icniccs of Mr*. John We mil uppn our tcpiiblicnn rcprc Died.

W i n t e r r e m e m b e r t h e W O O L L E N S. W rite to the M anageress RIDGE LAUNDRY, ST. H E LE N S. A uction Sale.

H A M M IG K S L IM IT E D, ' i. - I f

.-I;-;;, '.-irc'afr?*. P ublic Notices. TiffiATRE, H. aiety

Theory of Linear Systems Exercises. Luigi Palopoli and Daniele Fontanelli

Part IB. Further Analysis. Year

Identification in closed-loop, MISO identification, practical issues of identification

Representation of standard models: Transfer functions are often used to represent standard models of controllers and signal filters.

Use: Analysis of systems, simple convolution, shorthand for e jw, stability. Motivation easier to write. Or X(z) = Z {x(n)}

z-transform Chapter 6

Quick Overview: Complex Numbers

Chapter 7. Digital Control Systems

EE480.3 Digital Control Systems. Part 7. Controller Design I. - Pole Assignment Method

Module 6: Deadbeat Response Design Lecture Note 1

Overview of Complex Numbers

Roundoff Noise in Digital Feedback Control Systems

Chapter 10: Rational Functions and the Riemann Sphere. By a rational function we mean a function f which can be expressed in the form

Proof of a conjecture by Ðoković on the Poincaré series of the invariants of a binary form

into a discrete time function. Recall that the table of Laplace/z-transforms is constructed by (i) selecting to get

Algebraic Algorithm for 2D Stability Test Based on a Lyapunov Equation. Abstract

A sufficient condition for the existence of the Fourier transform of f : R C is. f(t) dt <. f(t) = 0 otherwise. dt =

EE Experiment 11 The Laplace Transform and Control System Characteristics

A Memorial. Death Crash Branch Out. Symbol The. at Crossing Flaming Poppy. in Belding

18.03 LECTURE NOTES, SPRING 2014

Chapter 5 THE APPLICATION OF THE Z TRANSFORM. 5.3 Stability

HEAGAN & CO., OPP. f>, L. & W. DEPOT, DOYER, N. J, OUR MOTTO! ould Iwv ia immediate vltlui. VEEY BEST NEW Creamery Butter 22c ib,

2. Complex Analytic Functions

Very useful for designing and analyzing signal processing systems

Discrete-time models and control

Properties of orthogonal polynomials

Symbolic Dynamics of Digital Signal Processing Systems

EE 3054: Signals, Systems, and Transforms Summer It is observed of some continuous-time LTI system that the input signal.

Lecture 04: Discrete Frequency Domain Analysis (z-transform)

EE480.3 Digital Control Systems. Part 2. z-transform

A L T O SOLO LOWCLL. MICHIGAN, THURSDAY. DECEMBER 10,1931. ritt. Mich., to T h e Heights. Bos" l u T H I S COMMl'NiTY IN Wilcox

EE102B Signal Processing and Linear Systems II. Solutions to Problem Set Nine Spring Quarter

Laplace Transforms. Chapter 3. Pierre Simon Laplace Born: 23 March 1749 in Beaumont-en-Auge, Normandy, France Died: 5 March 1827 in Paris, France

Circuits and Systems I

MA 412 Complex Analysis Final Exam

A DARK GREY P O N T, with a Switch Tail, and a small Star on the Forehead. Any

1. Find the Taylor series expansion about 0 of the following functions:

Math 460: Complex Analysis MWF 11am, Fulton Hall 425 Homework 8 Solutions Please write neatly, and in complete sentences when possible.

Chapter 15 - Solved Problems

Root Locus. Motivation Sketching Root Locus Examples. School of Mechanical Engineering Purdue University. ME375 Root Locus - 1

Damped Oscillators (revisited)

INTRODUCTION TO TRANSFER FUNCTIONS

ELEG 305: Digital Signal Processing

Considering our result for the sum and product of analytic functions, this means that for (a 0, a 1,..., a N ) C N+1, the polynomial.

CHAPTER 5: LAPLACE TRANSFORMS

Discrete-time first-order systems

Digital Control System

21.4. Engineering Applications of z-transforms. Introduction. Prerequisites. Learning Outcomes

Automatique. A. Hably 1. Commande d un robot mobile. Automatique. A.Hably. Digital implementation

Control Systems Lab - SC4070 System Identification and Linearization

ELEC2400 Signals & Systems

Chapter 11. Cauchy s Integral Formula

Complex Analysis Topic: Singularities

Discrete-time Controllers

Complex Analysis Qualifying Exam Solutions

Poles, Zeros and System Response

ENSC327 Communications Systems 2: Fourier Representations. Jie Liang School of Engineering Science Simon Fraser University

ENSC327 Communications Systems 2: Fourier Representations. School of Engineering Science Simon Fraser University

Lecture Note 3: Interpolation and Polynomial Approximation. Xiaoqun Zhang Shanghai Jiao Tong University

Analysis of Discrete-Time Systems

Transcription:

Chapter 12 - Solved Problems Solved Problem 12.1. The Z-transform of a signal f[k] is given by F q (z) = 2z6 z 5 + 3z 3 + 2z 2 z 7 + 2z 6 + z 5 + z 4 + 0.5 = n(z) d(z) where n(z) and d(z) are the numerator and denominator polynomials respectively Compute f[3]. Solutions to Solved Problem 12.1 (1) Solved Problem 12.2. Assume that the response of a discrete time system to a Kronecker delta (with zero initial conditions) is given by 12.2.1 Find the system transfer function. 12.2.2 Find the system recursive equation in shift operator form. Solutions to Solved Problem 12.2 h[k] = 2(0.5) k 2(0.2) k (2) Solved Problem 12.3. A discrete time system, with input u[k] and output y[k], has a transfer function given by z 0.8 z 2 1.3z + 0.42 Compute the unit step response with zero initial conditions. Solutions to Solved Problem 12.3 Solved Problem 12.4. The transfer function of a discrete time system is given by 0.5z (z + 0.5)(z 0.5) Compute, if it exists, the steady state response of the system to a unit constant input ( k 0) and initial conditions y[ 1] = 1, y[ 2] = 3. Solutions to Solved Problem 12.4 Solved Problem 12.5. A signal f(t) = 2 2 cos(2π t) is sampled every [s]. Compute the Z-transform of the sampled sequence f[k] for = 0.1 [s]. Solutions to Solved Problem 12.5 Solved Problem 12.6. Consider a continuous time transfer function s + 1 G o (s) = 3 (s + 1)(s + 3) Compute the associated pulse-transfer function, H oq (z), assuming that the sampling period is = 0.1 [s] and that a zero order hold is employed. (3) (4) (5) 1

Solutions to Solved Problem 12.6 Solved Problem 12.7. A discrete time system has a transfer function given by 0.1(z 0.2) (z 0.8)(z 0.9) (6) Assume that the input is a sine wave of the form u[k] = 2 cos(0.2πk). Compute the steady state output, y[k], if it exists. Solutions to Solved Problem 12.7 2

Chapter 12 - Solutions to Solved Problems Solution 12.1. To solve this problem we could compute the analytical expression for the inverse Z- transform, and then we could evaluate that expression at k = 3. An alternative method is to recall that F q (z) = f[0] + f[1]z 1 + f[2]z 2 + f[3]z 3 + f[4]z 4 +... (7) i.e., f[k] can be computed by expanding the fraction in (1) in powers of z 1. This can be done by dividing n(z) by d(z) up to the term z 3, its coefficient is equal to f[3]. The division can be performed using the MATLAB command deconv. This requires us to perform the division of z 3 n(z) by d(z). If we do that we obtain Therefore f[3] = 8. Solution 12.2. F q (z) = 2z 1 5z 2 + 8z 3 +... (8) 12.2.1 The transfer function is the Z-transform of the system response to a Kronecker delta (with zero initial conditions). Hence (use Table 12.1 in the book.) H q (z) = Z [h[k]] = 2z z 0.5 2z z 0.2 = 0.6z (z 0.5)(z 0.2) (9) This result can also be obtained using a symbolic mathematical software package, such as MAPLE. In this case, the MAPLE code would be >h(k):=2*(1/2)^ k-2*(1/5)^k; >H(z):=simplify(ztrans(h(k),k,z)); 12.2.2 Assuming that the system input is u[k] and the system output as y[k], with Z-transforms U q (z) and Y q (z), respectively, then Y q (z) U q (z) = H q(z) = z 2 Y q (z) 0.7zY q (z) + 0.1Y q (z) = 0.6zU q (z) (10) = Y q (z) 0.7z 1 Y q (z) + 0.1z 2 Y q (z) = 0.6z 1 U q (z) (11) = y[k]-0.7y[k-1]+0.1y[k-2]=0.6u[k-1] (12) Solution 12.3. The Z-transform of the input is given by U q (z) = z z 1 (13) 3

Then the Z-transform of the output is given by z 0.8 Y q (z) = z (z 0.6)(z 0.7)(z 1) }{{} Ỹ q(z) (14) If we expand Ỹq(z) in partial fractions 1 we have [ ] 5 Y q (z) = z 3(z 1) 5 z 0.6 + 10 3(z 0.7) = 5z 3(z 1) 5z z 0.6 + 10z 3(z 0.7) (15) Applying the inverse Z-transform we finally obtain y[k] = 5 3 µ[k] 5(0.6)k + 10 3 (0.7)k ; k 0 (16) Note the trick used in equation (15), where the whole expression has been factorized by z. This facilitates the computation of the inverse transform, otherwise a delay has to be introduced in the time function. The step response of a linear system can also be computed using a software package similar to MAPLE, using code similar to >Gq(z):=(z-0.8)/((z-0.6)*(z-0.7)); >invztrans(gq(z)*z/(z-1),z,k); Solution 12.4. The system has natural frequencies at 0.5 and 0.5, since both have magnitude less than one, then the system is stable. The system stability in conjunction with the nature of the input (a constant) yields an output which converges to a constant. Note that, in this case, the initial conditions have no effect whatsoever on the steady state behavior, since they only modify the initial amplitude of the natural modes, which vanish as time progresses. To compute the steady state value, we use the final value theorem (see Table 12.2 in the book), to obtain [ ] z y[ ] = lim(z 1)Y q (z) = lim(z 1) G q (1) = 2 z 1 z 1 z 1 3 (17) Note that G q (1) is the d.c. gain of the system. Solution 12.5. The sampled signal is given by f[k] = 2 2 cos(0.2πk) (18) Using Table 12.1 in the book we have that F q (z) = 2z z 1 2z(z cos(0.2π)) z 2 2z cos(0.2π) + 1 = 0.38z(z + 1.0) (z 1)(z 2 1.618z + 1) (19) 1 For this you can use the MATLAB command residue. 4

Solution 12.6. We first compute the unit step response of G o (s), this is given by [ ] [ ] g(t) = L 1 Go (s) = L 1 3( s + 1) (20) s (s + 1)(s + 3)s [ 1 = L 1 s 3 s + 1 + 2 ] = 1 3e t + 2e 3t (21) s + 3 To apply (12.13.4) from the book, we next need to compute the Z-transform of the sequence g[k] = g(k ): Z [g[k]] = Z [ 1 3(e ) + 2(e 3 ) ] (22) = z z 1 3z z e + 2z z e 3 = z z 1 3z z 0.9048 + 2z z 0.7408 (23) 0.2328 z + 0.2575 = z (z 1)(z 0.9048)(z 0.7408) (24) We are finally in position to apply (12.13.4) from the book. This yields H oq (z) = (1 z 1 )Z [g[k]] = 0.2328 z + 0.2575 (z 0.9048)(z 0.7408) (25) The above computation (very painful for a more complicated G o (s)) can be done using the MATLAB command c2d, as shown in the following code >>Go=tf([-3 3],[1 4 3]); >>Hoq=c2d(Go,0.1, zoh ) Solution 12.7. We observe that the system is stable (its poles are located inside the unit disk). Hence the steady state output can be computed using the frequency response concepts explained in section 12.15 of the book. Thus, the key quantity is G q (e jθ ) where, in this example, θ = 0.2π. This can be computed using the MATLAB command freqresp. G q (e j0.2π ) = 0.242e j2.51 = y[k] = 0.484 cos(0.2πk 2.51); in steady state (26) 5