STABILITY OF RESET SWITCHING SYSTEMS

Size: px
Start display at page:

Download "STABILITY OF RESET SWITCHING SYSTEMS"

Transcription

1 STABILITY OF RESET SWITCHING SYSTEMS J.P. Paxman,G.Vinnicombe Cambridge Universiy Engineering Deparmen, UK, Keywords: Sabiliy, swiching sysems, bumpless ransfer, conroller realizaion. Absrac In he design of swiching conrol sysems, he analysis of ransien signals is of umos imporance. Each ime a conrol ransfer akes place, he resuling ransien response may degrade performance. When swiching akes place rapidly, ineracion beween swiching ransiens may cause insabiliy even when each of he componen loops are sable aken separaely. We examine he issues of conroller realizaion and conroller iniializaion in he conex of swiching sysems. Our objecive is o minimize he performance degradaion caused by ransien signals a conroller ransiions, while guaraneeing sabiliy under arbirary swiching. Some heoreical ools are needed o analyze such sysems, where he saes are permied o change disconinuously a mode swiches. We consider a general Lyapunov funcion approach o analyze he sabiliy of rese swiching sysems, and use i o devise some LMI mehods for synhesizing sabilizing rese schemes. Inroducion When we design ideal linear conrollers (wihou swiching), he realizaion of conrollers is a relaively peripheral issue. Similarly he iniializaion of he conroller rarely meris much hough (zero is good enough mos of he ime). The reason is ha, once iniial ransiens have died down, only he inpuoupu ransfer funcions maer. Furhermore, if he plan sae is unknown a he iniial ime, i may be impossible o compue opimal conroller iniial saes in any case. In a conroller swiching conex, he issues of realizaion and iniializaion are crucialy imporan. A every conroller ransiion, new ransien signals are inroduced which are direcly relaed boh o he conroller realizaions and he conroller saes a swiching imes. Such ransien signals can degrade performance or even cause insabiliy. I is no difficul o consruc examples of swiching sysems where each componen sysem is sable, ye swiching may resul in unsable rajecories (see for example []). We can also consruc such examples in a conroller/plan framework. Tha is, we may swich beween sabilizing conrollers for a single (linear) plan in such a way ha he rajecories become unsable (see example.). All proofs appear in [7]. They are omied here for breviy. Conroller Iniializaion Suppose we have a family of sabilizing conrollers (wih given realizaions) for a paricular linear plan. If we swich beween hese conrollers, wha is he correc iniial sae when we swich o a new conroller? Naive approaches such as reseing o zero each ime, or having a coninuous common conroller sae (where he conrollers all have he same order) may resul in very poor performance or, in he wors case, insabiliy. We will inroduce a sysem of conroller reses, where he new conroller a each ransiion is iniialized by a funcion of he plan sae (eiher measured or observed) a ha ime. We do so in order o minimize (in some sense) he iniial sae ransien inroduced a each swich, while guaraneeing sabiliy.. Single swich Consider firs of all a single swich o a conroller K (from anoher conroller, or from manual conrol) a some ime. If we have a measuremen or observaion of he plan sae x G (), hen i is a sraighforward maer o minimize he iniial sae ransiens (in he finie or infinie horizon) wih respec o he conroller sae () according o some weighed cos funcion (see [6] for more deails). For example, suppose he closed loop sae space equaions can be wrien A x x G + A + Bu K y C x G + C, where y is a generalized oupu ha may include he plan inpu. The he minimum iniial sae ransien componen of y in he inerval [, ) occurs when he funcion V () y T (τ)y(τ)dτ. achieves a minimum, assuming u. The opimal conroller sae is hen () P P x G (), where P P P > P P is he soluion o he Lyapunov equaion A T P + PA C T C,

2 A [A A ], and C [C C ]. Tha is, he soluion is achieved a he minimum of he funcion V () x T ()Px() wih respec o he conroller sae () (which is a Lyapunov funcion for he sysem if C T C>). Similar soluions can also be obained by opimizing over weighed signals.. Rese swiching sysems If we now consider he arbirary swiching case, sabiliy is clearly a major concern. Since we have seen ha he use of conroller reses for swiching can improve performance, he nex quesion is wheher a sensible choice of conroller reses can sabilize an oherwise (poenially) unsable swiching sysem. For he sabiliy analysis we inroduce some Lyapunov funcion resuls for rese swiching sysems, where he sae of he sysem is permied o change disconinuously when he sysem swiches. Consider he family of linear vecor fields ẋ() A i x(), i I, x R n, () where I is some index se (ypically discree valued). Now define a piecewise consan swiching signal σ() σ() i k k < k+, i k I () for some sequence of swiching imes { k } and indices {i k } (k Z + ). We assume ha k < k+ and i k i k+ for all k. We define a linear rese swiching sysem by he equaions,i ẋ() A σ() x(), σ() i k, for k < k+, i k I, k Z +, x( + k )G i k k x( k ). () The linear funcions G i,j for i, j I are rese relaions beween he discree saes i and j. Noe ha when each of he rese relaions G i,j are ideniy, he coninuous sae is consrained o be coninuous across swiching imes. Such sysems are exensively analyzed in he lieraure. See for example [, ]. We will use he erm simple swiching sysem o disinguish such sysems from hose where rese relaions are applied. We shall choose an indexse I such ha he family of marices A i forms a compac se. We will denoe by S he se of all admissible swiching signals σ. We will assume in general ha he signals in S are non-zeno: ha is, here are a mos finiely many ransiions in any finie ime inerval. Theorem.. The rese swiching sysem () is uniformly asympoically sable for all admissible swiching signals σ S if and only if here exis a family of funcions V i : R n R wih he following properies: V i are posiive definie, decrescen and radially unbounded V i are coninuous and convex There exis consans c i such ha ( Vi (e Ai ) x) V (x) lim c i x + V j (G i,j x) V i (x) for all x R n, and i, j I. The heorem effecively saes ha sabiliy of he rese swiching sysem depends upon he exisence of a family of Lyapunov funcions for he separae vecor fields such ha a any swich on he swiching sysem, i is guaraneed ha he value of he new Lyapunov funcion afer he swich will be no larger han he value of he old funcion prior o he swich. The funcions are no necessarily differeniable everywhere, and so are of similar form o hose considered by Molchanov in [5]. Dayawansa and Marin [] proved ha a simple swiching sysem is sable for all swiching signals if and only if here exiss a common Lyapunov funcion for he componen sysems. Our heorem can be considered an exension of ha heorem o rese swiching sysems, and a similar consrucion is used o prove exisence. The funcions V i are no necessarily quadraic. Indeed, Dayawansa gives an example of a sable wo componen simple swiching sysem for which no quadraic common Lyapunov funcion exiss. I sill however makes sense o firs consider quadraic funcions in aemping o prove sabiliy of a swiching sysem. We can wrie he quadraic version of he heorem as he following sufficien condiion. Corollary.. The rese swiching sysem () is uniformly asympoically sable for all admissible swiching signals σ S if here exis a family of marices P i > wih he following properies: A T i P i + P i A i < G T i,j P jg i,j P i for all i, j I.. Plan/conroller srucure Now we consider a class of reses wih a paricular srucure. We are primarily ineresed in sysems where he componen vecor fields are made up of plan/conroller closed loops. The rese relaions we consider hen are such ha he plan sae remains consan across swiching boundaries, and he conroller sae only is rese. Specifically, we consider a family of N conrollers K i in a swiching arrangemen such ha a each insan one of K i are in feedback wih he plan G.

3 If G and K have he following sae-space represenaions AG B G G AKi B K i Ki, () C G D G C Ki D Ki hen he closed loop marices A i can be wrien Ai (, ) A A i A i (, ) A i (, ) AG + B : G D Ki C G B G C Ki. B Ki C G A Ki + B Ki D G C Ki The plan sae is x G wih dimension n G, and he conrollers K i have saes i wih dimensions n K. For simpliciy we resric consideraion o conrollers of he same dimension, however he resuls do in fac hold in general for conrollers of differen dimensions wih relaively sraighforward modificaions. We define he curren conroller sae o be () i () when σ() i, and he sae of he closed loop sysem is x. Suppose he reses are such ha he plan sae is coninuous, and he conroller sae is a linear funcion of plan sae. Tha is, we resric he marices G i,j o he form I G i,j (6) X i,j where X i,j R nk ng. We now make an imporan observaion. Remark.. Consider he rese swiching sysem (), wih rese marices wih srucure given in (6). If heorem. is saisfied, hen he Lyapunov funcions V i mus saisfy he condiion () argminv i X x j,i x G. K Pu anoher way, any family of such reses for which sabiliy is guaraneed mus minimize some Lyapunov funcions for he respecive subsysems. A furher consequence of his observaion is ha if G i,j are sabilizing reses of he form (6) and he argumens argminv i ([ ]) are unique, hen he marices X i,j and hence he G i,j can only depend on he index of he new dynamics j. This makes sense, since he fuure behaviour of he sysem is no dependen on he previous values of he swiching signal. We will wrie X i,j X j,andg i,j G j subsequenly when appropriae. (5) Now consider he poenially sabilizing reses G i of he form I G i, (7) X i () where X i x G argminv i,andv x i is a Lyapunov K funcion for he i h subsysem. Theorem.. Consider he rese swiching sysem (), wih rese marices wih srucure given in (7). The sysem is asympoically sable for all swiching signals σ S if and only if here exiss a family of funcions V i : R n R wih he following properies: V i are posiive definie, decrescen and radially unbounded V i are coninuous, wih coninuous parial dervaives There exis consans c i such ha ( Vi (e Ai ) x) V (x) lim c i x + V i are such ha X i x G argminv i ([ ]) for all x G R ng () () V j V X j x i G X i x G for all x G R ng and i, j I This heorem says ha for rese swiching sysem (of he form (7)) o be asympoically sable for all swiching signals, here mus exis Lyapunov funcions V i, such ha he level curves have he same projecion ino he plan subspace. We now have quie sric condiions which mus be me if a rese swiching sysem is o be sable for all admissible signals σ. I is a relaively sraighforward maer o es he condiion for quadraic Lyapunov funcions. An immediae consequence of he previous heorem is ha if he plan is firs order, and he family of reses X i are equivalen o he minimizaion of quadraic Lyapunov funcions for he i h loop, hen sabiliy is auomaically guaraneed. For plans of more han firs order, heorem. is difficul o saisfy for given reses. I does, however lead o a good mehod for synhesizing sabilizing reses for given sysems.. Rese synhesis for sabiliy For a se of given conrollers, we may ask he quesion of wheher a family of rese relaions exis which guaranee asympoic sabiliy for all swiching signals. We shall call such a family of reses asabilizing family of rese relaions.

4 I is a relaively sraighforward maer Compuaionally, we may easily o perform compuaions on While a general search for Lyapunov funcions which saisfy heorem. is a difficul problem, i is relaively sraighforward o find quadraic Lyapunov funcions, and he corresponding sabilizing reses if hey exis. The aim is o find a se of posiive definie marices Pi (, ) P P i P i (, ) P i (, ) such ha P i (, ) P P i (, ) P i (, ) P j (, ) P j (, )P j (, ) P j (, ) for all j i, and ha he Lyapunov inequaliies A T i P i + P i A i < are saisfied for all i. Using Schur complemens, we can now form an equivalen problem in erms of marices Q i where Q i Pi. Define P i (, ) P P i (, ) P i (, ). can be hough of as he inverse of he (, ) block of he inverse of P i, so he equivalen problem is o find posiive definie marices Q Q i Q T Q i (, ) saisfying Q i A T i + A i Q i < Then he required rese relaions are P i (, ) P i (, )x G, where P i Q i. Theorem.. Consider he coninuous-ime linear plan G, and N conrollers K i defined according o (), and le he closed loop marices Ai (, ) A A i A i (, ) A i (, ) be defined according o eqquaion (5). There exiss a sabilizing family of rese relaions when here exis marices, Q R ng nk and Q i (, ) R nki nk for each i {,...,N} such ha he following sysem of LMIs is saisfied: Φi (, ) Φ < (8) Φ i (, ) Φ i (, ) where Φ i (, ) A i (, ) T + Q A T + A i (, ) + A Q T, Φ A i (, ) T + Q A i (, ) T + A i (, )Q + A Q i (, ), Φ i (, ) Q T A i (, ) T + Q i (, )A T + A i (, ) + A i (, )Q T, Φ i (, ) Q T A i (, ) T + Q i (, )A i (, ) T + A i (, )Q + A i (, )Q i (, ). The rese relaions guaraneeing sabiliy are where P i P i (, ) P i (, ), Pi (, ) P P i (, ) P i (, ) Q Q T. Q i (, ) I is no always possible o find conroller reses which will guaranee sabiliy under arbirary swiching. This is rivially shown by consrucing an example of a dynamic plan wih wo saic gain conrollers, bu where no common Lyapunov funcion exiss. Since he conrollers have no sae, a rese canno help! We shall see however ha we can always consruc a non-minimal realizaion of he conrollers such ha sabilizing reses do exis. The rese resuls so far depend on precise knowledge of he plan sae. In fac he resuls hold if we rese based on observed plan saes, as long as he observer converges (ha is, he sysem is observable). Conroller realizaion Recen work by Hespanha and Morse [] considers he problem of selecion of appropriae realizaions for a family of sabilizing conrollers for a paricular process. They have shown ha i is possible o choose realizaions for families of sabilizing conrollers such ha he (simple) swiching sysem is sable under arbirary swiching. The scheme uses an inernal model conrol arrangemen, where he realized conroller conains a model of boh he plan and he desired closed loop. We can also realize conrollers o guaranee sabiliy by implemening he conrollers in a paricular coprime facor form. Suppose we have a plan G, and a se of sabilizing conrollers K i. We may choose a righ coprime facorizaion of he plan G NM, and lef coprime facorizaions of he conrollers K i V i U i, such ha for each i he bezou ideniy V i M + U i N I is saisfied. Furhermore given any Q such ha Q, Q RH, he facorizaions G Ñ M,andK i Ṽ i Ũ i also

5 ˆK σ Ũ û swiching poins swiching poins I Ṽ w Ũi ûi u P I Ṽi v Ũn ûn (a) Unsable rajecory (b) Coprime facor realizaion I Ṽn swiching poins swiching poins Figure : Swiching arrangemen saisfy he bezou ideniies Ṽ i M + Ũ i Ñ I, where Ñ NQ, M MQ,Ũi Q U i, and Ṽi Q V i. A paricular choice of Q for a conroller facorizaion can also be hough of as a paricular choice for he plan facorizaion (via Q), or vice versa. In he swiching conroller case, his is rue provided ha all of he conrollers have he same choice of Q. Now consider he coprime facor swiching arrangemen in figure. The swiching connecion is such ha u() û σ(), where σ() is he swiching signal governing he conroller selecion. The signals u, v, andw are common o he loops. We can hink of his sysem as a plan P in a feedback loop wih he augmened conroller ˆK σ. Noe ha for each loop i,wehave û i (I Ṽi)u ŨiPu ŨiPw+ Ũiv (I Ṽi ŨiÑ M )u ŨiPw+ Ũiv (M ṼiM ŨiÑ) M u ŨiPw+ Ũiv (I M )u ŨiPw+ Ũiv. Since u û σ, we can wrie and u (I M )u ŨσPw+ Ũσv MŨσPw+ MŨσv M(ŨσÑ) M w + MŨσv M(I Ṽσ M) M w + MŨσv (I MṼσ)w + MŨσv, y P (u + w) Ñ M (( (I MṼσ)w + MŨσv)+w) ÑṼσw + ÑŨσv (c) Coprime facor realizaions (Lyapunov based rese full sae knowledge) Figure : (d) Coprime facor realizaions (Lyapunov based rese, sae observer) We assume ha he signals w and v are bounded wih bounded wo norm, and we know all of he coprime facors are sable. Then he signals Ṽσw, Ṽσv, Ũσw, andũσv will all be bounded wih bounded wo norm. Hence u and y are bounded wih bounded wo norm, and he swiching sysem is sable for all admissible swiching sequences. We can wrie hese closed-loop relaionships in he compac form u (I MṼ σ ) MŨ σ w. y ÑṼσ ÑŨσ v The sabiliy of his swiching sysem is guaraneed since M, Ñ, and each Ũi and Ṽi are sable. Noe ha he saes of he conrollers evolve idenically irrespecive of which conroller is acive. This srucure is similar o ha employed in he work of Miyamoo and Vinnicombe [] for conrollers subjec o sauraion. In ha case, Q may be compued via an H opimizaion wihou reference o he conroller. Hence he same Q may be used o guaranee sabiliy in he swiching case. We may combine he resuls on conroller realizaion and iniializaion. The addiion of a rese arrangemen o a sysem of conrollers realized for sabiliy can resul in a subsanial performance improvemen as he following example shows. Example.. Take a second order lighly damped plan P (s) s +.s +

6 implemened in conroller canonical form ] [ [ẋ. ẋ y [ ] x, x x ] + [ ] u and wo saic sabilizing feedback gains k,andk. The closed loop equaions formed by seing u k (r y), and u k (r y) (where r is some reference) are respecively and ] [ẋ ẋ [. y [ ] x, x ] [ẋ ẋ ][ x ] + [ ] r [. 5 + r x ] y [ ] x. x We shall refer o he respecive sae-space marices as A, A, B and C. I is reasonably sraighforward o show ha while boh A and A have eigenvalues in he lef half plane, hey do no share a common quadraic Lyapunov funcion. The swiching sysem defined by ẋ A σ() x + Bu y Cx is herefore no guaraneed o be sable for all swiching signals σ(). Indeed, we can consruc a desabilizing signal by swiching from k o k when x is a maximum (for ha loop), and from k o k when x is a maximum. This produces he unsable sae rajecories shown in figure (a) from an iniial sae of x x, and zero reference. Since he conroller is saic, we obviously canno improve sabiliy by reseing conroller saes! We can, however implemen he conrollers in a non-minimal form, for which sabiliy can be guaraneed. We use here he coprime facor approach. When we implemen hese conrollers in he arrangemen of figure using he same iniial condiion and swiching crierion as before (he non-minimal are iniialized o zero), we obain he sable rajecory shown in figure (b). Noe however, ha he performance is poor and he saes ake over 5 seconds o converge. We now apply he resuls of heorem 8 o he loops formed by hese non-minimal conrollers. We find ha here exis as expeced, Lyapunov funcions of he respecive closed loops wih common projecion ino plan-space. Hence we can find a sabilizing conroller rese. This resuls in he sable rajecory shown in figure (c). Noe he performance improvemen obained by using he exra freedom in he conroller saes a he swiching imes. Since he rese scheme as applied for figure (c) requires full sae knowledge, i is no quie a fair comparison wih he (nonrese) coprime facor scheme. Therefore, we also implemen he resuls using a plan sae observer. The resuls, shown in figure (d) show ha while performance is slighly worse han he full-sae knowledge case, i is sill subsanially beer han he oher schemes. Conclusions We have inroduced a new Lyapunov sabiliy heorem which allows us o analyze sabiliy of swiching sysems where he sae is permied o rese a swiching imes. This primarily allows us o examine reses of he conroller in conroller swiching sysems. The heorem has a number of imporan consequences. Principally, i leads us o a mehod for synhesizing rese rules for a given swiching sysem, which hen guaranee sabiliy under arbirary swiching. This approach may also be combined wih mehods for realizing conrollers such ha sabiliy may be guaraneed for arbirary swiching, and performance subsanially improved. References [] W. P. Dayawansa and C. F. Marin. A converse Lyapunov heorem for a class of dynamical sysems which undergo swiching. IEEE Transacions on Auomaic Conrol, ():75 76, 999. [] J. P. Hespanha and A. S. Morse. Swiching beween sabilizing conrollers. Auomaica, 8(8):95 97,. [] D. Liberzon and A. S. Morse. Basic problems in sabiliy and design of swiched sysems. IEEE Conrol Sysems Magazine, 9(5):59 7, 999. [] S. Miyamoo and G. Vinnicombe. Robus conrol of plans wih sauraion nonlineariies based on coprime facor represenaions. In Proceedings IEEE Conference on Decision and Conrol, pages 88 8, Kobe, 996. [5] A. P Molchanov and Y. S Pyaniskiy. Lyapunov funcions ha specify necessary and sufficien condiions of absolue sabiliy of nonlinear nonsaionary conrol sysems, par i. Auomaion and Remoe Conrol, 7: 5, 986. [6] J. Paxman and G. Vinnicombe. Opimal ransfer schemes for swiching conrollers. In Proceedings IEEE Conference on Decision and Conrol, pages 9 98, Sydney,. [7] J. P. Paxman. Sabiliy of rese swiching sysems. Technical Repor CUED/F-INFENG/TR.6, Cambridge Universiy Engineering Deparmen, July. hp://wwwconrol.eng.cam.ac.uk/jpp7/rese.hml.

di Bernardo, M. (1995). A purely adaptive controller to synchronize and control chaotic systems.

di Bernardo, M. (1995). A purely adaptive controller to synchronize and control chaotic systems. di ernardo, M. (995). A purely adapive conroller o synchronize and conrol chaoic sysems. hps://doi.org/.6/375-96(96)8-x Early version, also known as pre-prin Link o published version (if available):.6/375-96(96)8-x

More information

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality Marix Versions of Some Refinemens of he Arihmeic-Geomeric Mean Inequaliy Bao Qi Feng and Andrew Tonge Absrac. We esablish marix versions of refinemens due o Alzer ], Carwrigh and Field 4], and Mercer 5]

More information

Lecture 20: Riccati Equations and Least Squares Feedback Control

Lecture 20: Riccati Equations and Least Squares Feedback Control 34-5 LINEAR SYSTEMS Lecure : Riccai Equaions and Leas Squares Feedback Conrol 5.6.4 Sae Feedback via Riccai Equaions A recursive approach in generaing he marix-valued funcion W ( ) equaion for i for he

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation:

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation: M ah 5 7 Fall 9 L ecure O c. 4, 9 ) Hamilon- J acobi Equaion: Weak S oluion We coninue he sudy of he Hamilon-Jacobi equaion: We have shown ha u + H D u) = R n, ) ; u = g R n { = }. ). In general we canno

More information

Hybrid Control and Switched Systems. Lecture #3 What can go wrong? Trajectories of hybrid systems

Hybrid Control and Switched Systems. Lecture #3 What can go wrong? Trajectories of hybrid systems Hybrid Conrol and Swiched Sysems Lecure #3 Wha can go wrong? Trajecories of hybrid sysems João P. Hespanha Universiy of California a Sana Barbara Summary 1. Trajecories of hybrid sysems: Soluion o a hybrid

More information

EXERCISES FOR SECTION 1.5

EXERCISES FOR SECTION 1.5 1.5 Exisence and Uniqueness of Soluions 43 20. 1 v c 21. 1 v c 1 2 4 6 8 10 1 2 2 4 6 8 10 Graph of approximae soluion obained using Euler s mehod wih = 0.1. Graph of approximae soluion obained using Euler

More information

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3 and d = c b - b c c d = c b - b c c This process is coninued unil he nh row has been compleed. The complee array of coefficiens is riangular. Noe ha in developing he array an enire row may be divided or

More information

Sliding Mode Extremum Seeking Control for Linear Quadratic Dynamic Game

Sliding Mode Extremum Seeking Control for Linear Quadratic Dynamic Game Sliding Mode Exremum Seeking Conrol for Linear Quadraic Dynamic Game Yaodong Pan and Ümi Özgüner ITS Research Group, AIST Tsukuba Eas Namiki --, Tsukuba-shi,Ibaraki-ken 5-856, Japan e-mail: pan.yaodong@ais.go.jp

More information

Model Reduction for Dynamical Systems Lecture 6

Model Reduction for Dynamical Systems Lecture 6 Oo-von-Guericke Universiä Magdeburg Faculy of Mahemaics Summer erm 07 Model Reducion for Dynamical Sysems ecure 6 v eer enner and ihong Feng Max lanck Insiue for Dynamics of Complex echnical Sysems Compuaional

More information

11!Hí MATHEMATICS : ERDŐS AND ULAM PROC. N. A. S. of decomposiion, properly speaking) conradics he possibiliy of defining a counably addiive real-valu

11!Hí MATHEMATICS : ERDŐS AND ULAM PROC. N. A. S. of decomposiion, properly speaking) conradics he possibiliy of defining a counably addiive real-valu ON EQUATIONS WITH SETS AS UNKNOWNS BY PAUL ERDŐS AND S. ULAM DEPARTMENT OF MATHEMATICS, UNIVERSITY OF COLORADO, BOULDER Communicaed May 27, 1968 We shall presen here a number of resuls in se heory concerning

More information

4. Advanced Stability Theory

4. Advanced Stability Theory Applied Nonlinear Conrol Nguyen an ien - 4 4 Advanced Sabiliy heory he objecive of his chaper is o presen sabiliy analysis for non-auonomous sysems 41 Conceps of Sabiliy for Non-Auonomous Sysems Equilibrium

More information

2. Nonlinear Conservation Law Equations

2. Nonlinear Conservation Law Equations . Nonlinear Conservaion Law Equaions One of he clear lessons learned over recen years in sudying nonlinear parial differenial equaions is ha i is generally no wise o ry o aack a general class of nonlinear

More information

A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS

A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS Xinping Guan ;1 Fenglei Li Cailian Chen Insiue of Elecrical Engineering, Yanshan Universiy, Qinhuangdao, 066004, China. Deparmen

More information

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions Muli-Period Sochasic Models: Opimali of (s, S) Polic for -Convex Objecive Funcions Consider a seing similar o he N-sage newsvendor problem excep ha now here is a fixed re-ordering cos (> 0) for each (re-)order.

More information

STATE-SPACE MODELLING. A mass balance across the tank gives:

STATE-SPACE MODELLING. A mass balance across the tank gives: B. Lennox and N.F. Thornhill, 9, Sae Space Modelling, IChemE Process Managemen and Conrol Subjec Group Newsleer STE-SPACE MODELLING Inroducion: Over he pas decade or so here has been an ever increasing

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

E β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem.

E β t log (C t ) + M t M t 1. = Y t + B t 1 P t. B t 0 (3) v t = P tc t M t Question 1. Find the FOC s for an optimum in the agent s problem. Noes, M. Krause.. Problem Se 9: Exercise on FTPL Same model as in paper and lecure, only ha one-period govenmen bonds are replaced by consols, which are bonds ha pay one dollar forever. I has curren marke

More information

Mean-square Stability Control for Networked Systems with Stochastic Time Delay

Mean-square Stability Control for Networked Systems with Stochastic Time Delay JOURNAL OF SIMULAION VOL. 5 NO. May 7 Mean-square Sabiliy Conrol for Newored Sysems wih Sochasic ime Delay YAO Hejun YUAN Fushun School of Mahemaics and Saisics Anyang Normal Universiy Anyang Henan. 455

More information

Laplace Transform and its Relation to Fourier Transform

Laplace Transform and its Relation to Fourier Transform Chaper 6 Laplace Transform and is Relaion o Fourier Transform (A Brief Summary) Gis of he Maer 2 Domains of Represenaion Represenaion of signals and sysems Time Domain Coninuous Discree Time Time () [n]

More information

Optimality Conditions for Unconstrained Problems

Optimality Conditions for Unconstrained Problems 62 CHAPTER 6 Opimaliy Condiions for Unconsrained Problems 1 Unconsrained Opimizaion 11 Exisence Consider he problem of minimizing he funcion f : R n R where f is coninuous on all of R n : P min f(x) x

More information

Boundedness and Exponential Asymptotic Stability in Dynamical Systems with Applications to Nonlinear Differential Equations with Unbounded Terms

Boundedness and Exponential Asymptotic Stability in Dynamical Systems with Applications to Nonlinear Differential Equations with Unbounded Terms Advances in Dynamical Sysems and Applicaions. ISSN 0973-531 Volume Number 1 007, pp. 107 11 Research India Publicaions hp://www.ripublicaion.com/adsa.hm Boundedness and Exponenial Asympoic Sabiliy in Dynamical

More information

The Asymptotic Behavior of Nonoscillatory Solutions of Some Nonlinear Dynamic Equations on Time Scales

The Asymptotic Behavior of Nonoscillatory Solutions of Some Nonlinear Dynamic Equations on Time Scales Advances in Dynamical Sysems and Applicaions. ISSN 0973-5321 Volume 1 Number 1 (2006, pp. 103 112 c Research India Publicaions hp://www.ripublicaion.com/adsa.hm The Asympoic Behavior of Nonoscillaory Soluions

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

Georey E. Hinton. University oftoronto. Technical Report CRG-TR February 22, Abstract

Georey E. Hinton. University oftoronto.   Technical Report CRG-TR February 22, Abstract Parameer Esimaion for Linear Dynamical Sysems Zoubin Ghahramani Georey E. Hinon Deparmen of Compuer Science Universiy oftorono 6 King's College Road Torono, Canada M5S A4 Email: zoubin@cs.orono.edu Technical

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

(1) (2) Differentiation of (1) and then substitution of (3) leads to. Therefore, we will simply consider the second-order linear system given by (4)

(1) (2) Differentiation of (1) and then substitution of (3) leads to. Therefore, we will simply consider the second-order linear system given by (4) Phase Plane Analysis of Linear Sysems Adaped from Applied Nonlinear Conrol by Sloine and Li The general form of a linear second-order sysem is a c b d From and b bc d a Differeniaion of and hen subsiuion

More information

Let us start with a two dimensional case. We consider a vector ( x,

Let us start with a two dimensional case. We consider a vector ( x, Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our

More information

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t... Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger

More information

Problemas das Aulas Práticas

Problemas das Aulas Práticas Mesrado Inegrado em Engenharia Elecroécnica e de Compuadores Conrolo em Espaço de Esados Problemas das Aulas Práicas J. Miranda Lemos Fevereiro de 3 Translaed o English by José Gaspar, 6 J. M. Lemos, IST

More information

SOME MORE APPLICATIONS OF THE HAHN-BANACH THEOREM

SOME MORE APPLICATIONS OF THE HAHN-BANACH THEOREM SOME MORE APPLICATIONS OF THE HAHN-BANACH THEOREM FRANCISCO JAVIER GARCÍA-PACHECO, DANIELE PUGLISI, AND GUSTI VAN ZYL Absrac We give a new proof of he fac ha equivalen norms on subspaces can be exended

More information

EE363 homework 1 solutions

EE363 homework 1 solutions EE363 Prof. S. Boyd EE363 homework 1 soluions 1. LQR for a riple accumulaor. We consider he sysem x +1 = Ax + Bu, y = Cx, wih 1 1 A = 1 1, B =, C = [ 1 ]. 1 1 This sysem has ransfer funcion H(z) = (z 1)

More information

Application of a Stochastic-Fuzzy Approach to Modeling Optimal Discrete Time Dynamical Systems by Using Large Scale Data Processing

Application of a Stochastic-Fuzzy Approach to Modeling Optimal Discrete Time Dynamical Systems by Using Large Scale Data Processing Applicaion of a Sochasic-Fuzzy Approach o Modeling Opimal Discree Time Dynamical Sysems by Using Large Scale Daa Processing AA WALASZE-BABISZEWSA Deparmen of Compuer Engineering Opole Universiy of Technology

More information

Math 10B: Mock Mid II. April 13, 2016

Math 10B: Mock Mid II. April 13, 2016 Name: Soluions Mah 10B: Mock Mid II April 13, 016 1. ( poins) Sae, wih jusificaion, wheher he following saemens are rue or false. (a) If a 3 3 marix A saisfies A 3 A = 0, hen i canno be inverible. True.

More information

Some Ramsey results for the n-cube

Some Ramsey results for the n-cube Some Ramsey resuls for he n-cube Ron Graham Universiy of California, San Diego Jozsef Solymosi Universiy of Briish Columbia, Vancouver, Canada Absrac In his noe we esablish a Ramsey-ype resul for cerain

More information

Math 334 Fall 2011 Homework 11 Solutions

Math 334 Fall 2011 Homework 11 Solutions Dec. 2, 2 Mah 334 Fall 2 Homework Soluions Basic Problem. Transform he following iniial value problem ino an iniial value problem for a sysem: u + p()u + q() u g(), u() u, u () v. () Soluion. Le v u. Then

More information

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2.

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2. THE BERNOULLI NUMBERS The Bernoulli numbers are defined here by he exponenial generaing funcion ( e The firs one is easy o compue: (2 and (3 B 0 lim 0 e lim, 0 e ( d B lim 0 d e +e e lim 0 (e 2 lim 0 2(e

More information

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004 ODEs II, Lecure : Homogeneous Linear Sysems - I Mike Raugh March 8, 4 Inroducion. In he firs lecure we discussed a sysem of linear ODEs for modeling he excreion of lead from he human body, saw how o ransform

More information

14 Autoregressive Moving Average Models

14 Autoregressive Moving Average Models 14 Auoregressive Moving Average Models In his chaper an imporan parameric family of saionary ime series is inroduced, he family of he auoregressive moving average, or ARMA, processes. For a large class

More information

Chapter 3 Boundary Value Problem

Chapter 3 Boundary Value Problem Chaper 3 Boundary Value Problem A boundary value problem (BVP) is a problem, ypically an ODE or a PDE, which has values assigned on he physical boundary of he domain in which he problem is specified. Le

More information

On Robust Stability of Uncertain Neutral Systems with Discrete and Distributed Delays

On Robust Stability of Uncertain Neutral Systems with Discrete and Distributed Delays 009 American Conrol Conference Hya Regency Riverfron S. Louis MO USA June 0-009 FrC09.5 On Robus Sabiliy of Uncerain Neural Sysems wih Discree and Disribued Delays Jian Sun Jie Chen G.P. Liu Senior Member

More information

IMPLICIT AND INVERSE FUNCTION THEOREMS PAUL SCHRIMPF 1 OCTOBER 25, 2013

IMPLICIT AND INVERSE FUNCTION THEOREMS PAUL SCHRIMPF 1 OCTOBER 25, 2013 IMPLICI AND INVERSE FUNCION HEOREMS PAUL SCHRIMPF 1 OCOBER 25, 213 UNIVERSIY OF BRIISH COLUMBIA ECONOMICS 526 We have exensively sudied how o solve sysems of linear equaions. We know how o check wheher

More information

Lecture 4 Notes (Little s Theorem)

Lecture 4 Notes (Little s Theorem) Lecure 4 Noes (Lile s Theorem) This lecure concerns one of he mos imporan (and simples) heorems in Queuing Theory, Lile s Theorem. More informaion can be found in he course book, Bersekas & Gallagher,

More information

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t M ah 5 2 7 Fall 2 0 0 9 L ecure 1 0 O c. 7, 2 0 0 9 Hamilon- J acobi Equaion: Explici Formulas In his lecure we ry o apply he mehod of characerisics o he Hamilon-Jacobi equaion: u + H D u, x = 0 in R n

More information

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux

Guest Lectures for Dr. MacFarlane s EE3350 Part Deux Gues Lecures for Dr. MacFarlane s EE3350 Par Deux Michael Plane Mon., 08-30-2010 Wrie name in corner. Poin ou his is a review, so I will go faser. Remind hem o go lisen o online lecure abou geing an A

More information

This document was generated at 1:04 PM, 09/10/13 Copyright 2013 Richard T. Woodward. 4. End points and transversality conditions AGEC

This document was generated at 1:04 PM, 09/10/13 Copyright 2013 Richard T. Woodward. 4. End points and transversality conditions AGEC his documen was generaed a 1:4 PM, 9/1/13 Copyrigh 213 Richard. Woodward 4. End poins and ransversaliy condiions AGEC 637-213 F z d Recall from Lecure 3 ha a ypical opimal conrol problem is o maimize (,,

More information

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon 3..3 INRODUCION O DYNAMIC OPIMIZAION: DISCREE IME PROBLEMS A. he Hamilonian and Firs-Order Condiions in a Finie ime Horizon Define a new funcion, he Hamilonian funcion, H. H he change in he oal value of

More information

Ordinary Differential Equations

Ordinary Differential Equations Ordinary Differenial Equaions 5. Examples of linear differenial equaions and heir applicaions We consider some examples of sysems of linear differenial equaions wih consan coefficiens y = a y +... + a

More information

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is UNIT IMPULSE RESPONSE, UNIT STEP RESPONSE, STABILITY. Uni impulse funcion (Dirac dela funcion, dela funcion) rigorously defined is no sricly a funcion, bu disribuion (or measure), precise reamen requires

More information

SOLUTIONS TO ECE 3084

SOLUTIONS TO ECE 3084 SOLUTIONS TO ECE 384 PROBLEM 2.. For each sysem below, specify wheher or no i is: (i) memoryless; (ii) causal; (iii) inverible; (iv) linear; (v) ime invarian; Explain your reasoning. If he propery is no

More information

Orthogonal Rational Functions, Associated Rational Functions And Functions Of The Second Kind

Orthogonal Rational Functions, Associated Rational Functions And Functions Of The Second Kind Proceedings of he World Congress on Engineering 2008 Vol II Orhogonal Raional Funcions, Associaed Raional Funcions And Funcions Of The Second Kind Karl Deckers and Adhemar Bulheel Absrac Consider he sequence

More information

Linear Quadratic Regulator (LQR) - State Feedback Design

Linear Quadratic Regulator (LQR) - State Feedback Design Linear Quadrai Regulaor (LQR) - Sae Feedbak Design A sysem is expressed in sae variable form as x = Ax + Bu n m wih x( ) R, u( ) R and he iniial ondiion x() = x A he sabilizaion problem using sae variable

More information

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes Some common engineering funcions 2.7 Inroducion This secion provides a caalogue of some common funcions ofen used in Science and Engineering. These include polynomials, raional funcions, he modulus funcion

More information

4 Sequences of measurable functions

4 Sequences of measurable functions 4 Sequences of measurable funcions 1. Le (Ω, A, µ) be a measure space (complee, afer a possible applicaion of he compleion heorem). In his chaper we invesigae relaions beween various (nonequivalen) convergences

More information

Lecture Notes 2. The Hilbert Space Approach to Time Series

Lecture Notes 2. The Hilbert Space Approach to Time Series Time Series Seven N. Durlauf Universiy of Wisconsin. Basic ideas Lecure Noes. The Hilber Space Approach o Time Series The Hilber space framework provides a very powerful language for discussing he relaionship

More information

Second Order Linear Differential Equations

Second Order Linear Differential Equations Second Order Linear Differenial Equaions Second order linear equaions wih consan coefficiens; Fundamenal soluions; Wronskian; Exisence and Uniqueness of soluions; he characerisic equaion; soluions of homogeneous

More information

Expert Advice for Amateurs

Expert Advice for Amateurs Exper Advice for Amaeurs Ernes K. Lai Online Appendix - Exisence of Equilibria The analysis in his secion is performed under more general payoff funcions. Wihou aking an explici form, he payoffs of he

More information

LAPLACE TRANSFORM AND TRANSFER FUNCTION

LAPLACE TRANSFORM AND TRANSFER FUNCTION CHBE320 LECTURE V LAPLACE TRANSFORM AND TRANSFER FUNCTION Professor Dae Ryook Yang Spring 2018 Dep. of Chemical and Biological Engineering 5-1 Road Map of he Lecure V Laplace Transform and Transfer funcions

More information

Technical Report Doc ID: TR March-2013 (Last revision: 23-February-2016) On formulating quadratic functions in optimization models.

Technical Report Doc ID: TR March-2013 (Last revision: 23-February-2016) On formulating quadratic functions in optimization models. Technical Repor Doc ID: TR--203 06-March-203 (Las revision: 23-Februar-206) On formulaing quadraic funcions in opimizaion models. Auhor: Erling D. Andersen Convex quadraic consrains quie frequenl appear

More information

T L. t=1. Proof of Lemma 1. Using the marginal cost accounting in Equation(4) and standard arguments. t )+Π RB. t )+K 1(Q RB

T L. t=1. Proof of Lemma 1. Using the marginal cost accounting in Equation(4) and standard arguments. t )+Π RB. t )+K 1(Q RB Elecronic Companion EC.1. Proofs of Technical Lemmas and Theorems LEMMA 1. Le C(RB) be he oal cos incurred by he RB policy. Then we have, T L E[C(RB)] 3 E[Z RB ]. (EC.1) Proof of Lemma 1. Using he marginal

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details!

Finish reading Chapter 2 of Spivak, rereading earlier sections as necessary. handout and fill in some missing details! MAT 257, Handou 6: Ocober 7-2, 20. I. Assignmen. Finish reading Chaper 2 of Spiva, rereading earlier secions as necessary. handou and fill in some missing deails! II. Higher derivaives. Also, read his

More information

Stability and Bifurcation in a Neural Network Model with Two Delays

Stability and Bifurcation in a Neural Network Model with Two Delays Inernaional Mahemaical Forum, Vol. 6, 11, no. 35, 175-1731 Sabiliy and Bifurcaion in a Neural Nework Model wih Two Delays GuangPing Hu and XiaoLing Li School of Mahemaics and Physics, Nanjing Universiy

More information

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1

SZG Macro 2011 Lecture 3: Dynamic Programming. SZG macro 2011 lecture 3 1 SZG Macro 2011 Lecure 3: Dynamic Programming SZG macro 2011 lecure 3 1 Background Our previous discussion of opimal consumpion over ime and of opimal capial accumulaion sugges sudying he general decision

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

5. Stochastic processes (1)

5. Stochastic processes (1) Lec05.pp S-38.45 - Inroducion o Teleraffic Theory Spring 2005 Conens Basic conceps Poisson process 2 Sochasic processes () Consider some quaniy in a eleraffic (or any) sysem I ypically evolves in ime randomly

More information

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 17

Designing Information Devices and Systems I Spring 2019 Lecture Notes Note 17 EES 16A Designing Informaion Devices and Sysems I Spring 019 Lecure Noes Noe 17 17.1 apaciive ouchscreen In he las noe, we saw ha a capacior consiss of wo pieces on conducive maerial separaed by a nonconducive

More information

Solutions from Chapter 9.1 and 9.2

Solutions from Chapter 9.1 and 9.2 Soluions from Chaper 9 and 92 Secion 9 Problem # This basically boils down o an exercise in he chain rule from calculus We are looking for soluions of he form: u( x) = f( k x c) where k x R 3 and k is

More information

The following report makes use of the process from Chapter 2 in Dr. Cumming s thesis.

The following report makes use of the process from Chapter 2 in Dr. Cumming s thesis. Zaleski 1 Joseph Zaleski Mah 451H Final Repor Conformal Mapping Mehods and ZST Hele Shaw Flow Inroducion The Hele Shaw problem has been sudied using linear sabiliy analysis and numerical mehods, bu a novel

More information

MEI STRUCTURED MATHEMATICS 4758

MEI STRUCTURED MATHEMATICS 4758 OXFORD CAMBRIDGE AND RSA EXAMINATIONS Advanced Subsidiary General Cerificae of Educaion Advanced General Cerificae of Educaion MEI STRUCTURED MATHEMATICS 4758 Differenial Equaions Thursday 5 JUNE 006 Afernoon

More information

Predator - Prey Model Trajectories and the nonlinear conservation law

Predator - Prey Model Trajectories and the nonlinear conservation law Predaor - Prey Model Trajecories and he nonlinear conservaion law James K. Peerson Deparmen of Biological Sciences and Deparmen of Mahemaical Sciences Clemson Universiy Ocober 28, 213 Ouline Drawing Trajecories

More information

SPECTRAL EVOLUTION OF A ONE PARAMETER EXTENSION OF A REAL SYMMETRIC TOEPLITZ MATRIX* William F. Trench. SIAM J. Matrix Anal. Appl. 11 (1990),

SPECTRAL EVOLUTION OF A ONE PARAMETER EXTENSION OF A REAL SYMMETRIC TOEPLITZ MATRIX* William F. Trench. SIAM J. Matrix Anal. Appl. 11 (1990), SPECTRAL EVOLUTION OF A ONE PARAMETER EXTENSION OF A REAL SYMMETRIC TOEPLITZ MATRIX* William F Trench SIAM J Marix Anal Appl 11 (1990), 601-611 Absrac Le T n = ( i j ) n i,j=1 (n 3) be a real symmeric

More information

Comments on Window-Constrained Scheduling

Comments on Window-Constrained Scheduling Commens on Window-Consrained Scheduling Richard Wes Member, IEEE and Yuing Zhang Absrac This shor repor clarifies he behavior of DWCS wih respec o Theorem 3 in our previously published paper [1], and describes

More information

12: AUTOREGRESSIVE AND MOVING AVERAGE PROCESSES IN DISCRETE TIME. Σ j =

12: AUTOREGRESSIVE AND MOVING AVERAGE PROCESSES IN DISCRETE TIME. Σ j = 1: AUTOREGRESSIVE AND MOVING AVERAGE PROCESSES IN DISCRETE TIME Moving Averages Recall ha a whie noise process is a series { } = having variance σ. The whie noise process has specral densiy f (λ) = of

More information

Morning Time: 1 hour 30 minutes Additional materials (enclosed):

Morning Time: 1 hour 30 minutes Additional materials (enclosed): ADVANCED GCE 78/0 MATHEMATICS (MEI) Differenial Equaions THURSDAY JANUARY 008 Morning Time: hour 30 minues Addiional maerials (enclosed): None Addiional maerials (required): Answer Bookle (8 pages) Graph

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

Properties Of Solutions To A Generalized Liénard Equation With Forcing Term

Properties Of Solutions To A Generalized Liénard Equation With Forcing Term Applied Mahemaics E-Noes, 8(28), 4-44 c ISSN 67-25 Available free a mirror sies of hp://www.mah.nhu.edu.w/ amen/ Properies Of Soluions To A Generalized Liénard Equaion Wih Forcing Term Allan Kroopnick

More information

POSITIVE SOLUTIONS OF NEUTRAL DELAY DIFFERENTIAL EQUATION

POSITIVE SOLUTIONS OF NEUTRAL DELAY DIFFERENTIAL EQUATION Novi Sad J. Mah. Vol. 32, No. 2, 2002, 95-108 95 POSITIVE SOLUTIONS OF NEUTRAL DELAY DIFFERENTIAL EQUATION Hajnalka Péics 1, János Karsai 2 Absrac. We consider he scalar nonauonomous neural delay differenial

More information

Class Meeting # 10: Introduction to the Wave Equation

Class Meeting # 10: Introduction to the Wave Equation MATH 8.5 COURSE NOTES - CLASS MEETING # 0 8.5 Inroducion o PDEs, Fall 0 Professor: Jared Speck Class Meeing # 0: Inroducion o he Wave Equaion. Wha is he wave equaion? The sandard wave equaion for a funcion

More information

Matlab and Python programming: how to get started

Matlab and Python programming: how to get started Malab and Pyhon programming: how o ge sared Equipping readers he skills o wrie programs o explore complex sysems and discover ineresing paerns from big daa is one of he main goals of his book. In his chaper,

More information

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively:

( ) a system of differential equations with continuous parametrization ( T = R + These look like, respectively: XIII. DIFFERENCE AND DIFFERENTIAL EQUATIONS Ofen funcions, or a sysem of funcion, are paramerized in erms of some variable, usually denoed as and inerpreed as ime. The variable is wrien as a funcion of

More information

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation

Course Notes for EE227C (Spring 2018): Convex Optimization and Approximation Course Noes for EE7C Spring 018: Convex Opimizaion and Approximaion Insrucor: Moriz Hard Email: hard+ee7c@berkeley.edu Graduae Insrucor: Max Simchowiz Email: msimchow+ee7c@berkeley.edu Ocober 15, 018 3

More information

Feedback design using nonsmooth control Lyapunov functions: A numerical case study for the nonholonomic integrator

Feedback design using nonsmooth control Lyapunov functions: A numerical case study for the nonholonomic integrator Feedback design using nonsmooh conrol Lyapunov funcions: A numerical case sudy for he nonholonomic inegraor Philipp Braun,2, Lars Grüne, Chrisopher M. Kelle 2 Absrac Theoreical resuls for he exisence of

More information

An Introduction to Backward Stochastic Differential Equations (BSDEs) PIMS Summer School 2016 in Mathematical Finance.

An Introduction to Backward Stochastic Differential Equations (BSDEs) PIMS Summer School 2016 in Mathematical Finance. 1 An Inroducion o Backward Sochasic Differenial Equaions (BSDEs) PIMS Summer School 2016 in Mahemaical Finance June 25, 2016 Chrisoph Frei cfrei@ualbera.ca This inroducion is based on Touzi [14], Bouchard

More information

SUFFICIENT CONDITIONS FOR EXISTENCE SOLUTION OF LINEAR TWO-POINT BOUNDARY PROBLEM IN MINIMIZATION OF QUADRATIC FUNCTIONAL

SUFFICIENT CONDITIONS FOR EXISTENCE SOLUTION OF LINEAR TWO-POINT BOUNDARY PROBLEM IN MINIMIZATION OF QUADRATIC FUNCTIONAL HE PUBLISHING HOUSE PROCEEDINGS OF HE ROMANIAN ACADEMY, Series A, OF HE ROMANIAN ACADEMY Volume, Number 4/200, pp 287 293 SUFFICIEN CONDIIONS FOR EXISENCE SOLUION OF LINEAR WO-POIN BOUNDARY PROBLEM IN

More information

INDEX. Transient analysis 1 Initial Conditions 1

INDEX. Transient analysis 1 Initial Conditions 1 INDEX Secion Page Transien analysis 1 Iniial Condiions 1 Please inform me of your opinion of he relaive emphasis of he review maerial by simply making commens on his page and sending i o me a: Frank Mera

More information

= ( ) ) or a system of differential equations with continuous parametrization (T = R

= ( ) ) or a system of differential equations with continuous parametrization (T = R XIII. DIFFERENCE AND DIFFERENTIAL EQUATIONS Ofen funcions, or a sysem of funcion, are paramerized in erms of some variable, usually denoed as and inerpreed as ime. The variable is wrien as a funcion of

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0.

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0. Time-Domain Sysem Analysis Coninuous Time. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 1. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 2 Le a sysem be described by a 2 y ( ) + a 1

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

arxiv: v1 [cs.sy] 22 Dec 2018

arxiv: v1 [cs.sy] 22 Dec 2018 ON ASYMPTOTIC CHARACTERIZATION OF DESTABILIZING SWITCHING SIGNALS FOR SWITCHED LINEAR SYSTEMS ATREYEE KUNDU arxiv:181.09504v1 [cs.sy] Dec 018 Absrac. This paper deals wih classes of desabilizing swiching

More information

THE GENERALIZED PASCAL MATRIX VIA THE GENERALIZED FIBONACCI MATRIX AND THE GENERALIZED PELL MATRIX

THE GENERALIZED PASCAL MATRIX VIA THE GENERALIZED FIBONACCI MATRIX AND THE GENERALIZED PELL MATRIX J Korean Mah Soc 45 008, No, pp 479 49 THE GENERALIZED PASCAL MATRIX VIA THE GENERALIZED FIBONACCI MATRIX AND THE GENERALIZED PELL MATRIX Gwang-yeon Lee and Seong-Hoon Cho Reprined from he Journal of he

More information

Econ107 Applied Econometrics Topic 7: Multicollinearity (Studenmund, Chapter 8)

Econ107 Applied Econometrics Topic 7: Multicollinearity (Studenmund, Chapter 8) I. Definiions and Problems A. Perfec Mulicollineariy Econ7 Applied Economerics Topic 7: Mulicollineariy (Sudenmund, Chaper 8) Definiion: Perfec mulicollineariy exiss in a following K-variable regression

More information

The L p -Version of the Generalized Bohl Perron Principle for Vector Equations with Infinite Delay

The L p -Version of the Generalized Bohl Perron Principle for Vector Equations with Infinite Delay Advances in Dynamical Sysems and Applicaions ISSN 973-5321, Volume 6, Number 2, pp. 177 184 (211) hp://campus.ms.edu/adsa The L p -Version of he Generalized Bohl Perron Principle for Vecor Equaions wih

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

MATH 5720: Gradient Methods Hung Phan, UMass Lowell October 4, 2018

MATH 5720: Gradient Methods Hung Phan, UMass Lowell October 4, 2018 MATH 5720: Gradien Mehods Hung Phan, UMass Lowell Ocober 4, 208 Descen Direcion Mehods Consider he problem min { f(x) x R n}. The general descen direcions mehod is x k+ = x k + k d k where x k is he curren

More information

Appendix 14.1 The optimal control problem and its solution using

Appendix 14.1 The optimal control problem and its solution using 1 Appendix 14.1 he opimal conrol problem and is soluion using he maximum principle NOE: Many occurrences of f, x, u, and in his file (in equaions or as whole words in ex) are purposefully in bold in order

More information