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Linear Systems Theory: Second Edition Second Edition [Kõva köide]

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  • Formaat: Hardback, 352 pages, kõrgus x laius: 254x203 mm, kaal: 964 g, 52 b/w illus.
  • Ilmumisaeg: 13-Feb-2018
  • Kirjastus: Princeton University Press
  • ISBN-10: 0691179573
  • ISBN-13: 9780691179575
Teised raamatud teemal:
Linear Systems Theory: Second Edition Second EditionSuurem pilt
  • Formaat: Hardback, 352 pages, kõrgus x laius: 254x203 mm, kaal: 964 g, 52 b/w illus.
  • Ilmumisaeg: 13-Feb-2018
  • Kirjastus: Princeton University Press
  • ISBN-10: 0691179573
  • ISBN-13: 9780691179575
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780691179575.html
Märksõnad:
A fully updated textbook on linear systems theory

Linear systems theory is the cornerstone of control theory and a well-established discipline that focuses on linear differential equations from the perspective of control and estimation. This updated second edition of Linear Systems Theory covers the subject's key topics in a unique lecture-style format, making the book easy to use for instructors and students. João Hespanha looks at system representation, stability, controllability and state feedback, observability and state estimation, and realization theory. He provides the background for advanced modern control design techniques and feedback linearization and examines advanced foundational topics, such as multivariable poles and zeros and LQG/LQR. 

The textbook presents only the most essential mathematical derivations and places comments, discussion, and terminology in sidebars so that readers can follow the core material easily and without distraction. Annotated proofs with sidebars explain the techniques of proof construction, including contradiction, contraposition, cycles of implications to prove equivalence, and the difference between necessity and sufficiency. Annotated theoretical developments also use sidebars to discuss relevant commands available in MATLAB, allowing students to understand these tools. This second edition contains a large number of new practice exercises with solutions. Based on typical problems, these exercises guide students to succinct and precise answers, helping to clarify issues and consolidate knowledge. The book's balanced chapters can each be covered in approximately two hours of lecture time, simplifying course planning and student review. 







Easy-to-use textbook in unique lecture-style format Sidebars explain topics in further detail Annotated proofs and discussions of MATLAB commands Balanced chapters can each be taught in two hours of course lecture New practice exercises with solutions included

Arvustused

"Praise for the previous edition: "Linear Systems Theory gives a good presentation of the main topics on linear systems as well as more advanced topics related to controller design. The scholarship is sound and the book is very well written and readable.""---Ian Petersen, University of New South Wales "Praise for the previous edition: "This book provides a sound basis for an excellent course on linear systems theory. It covers a breadth of material in a fast-paced and mathematically focused way. It can be used by students wishing to specialize in this subject, as well as by those interested in this topic generally.""---Geir E. Dullerud, University of Illinois, Urbana-Champaign

Preamble xiii
Linear Systems I Basic Concepts 1(220)
I System Representation
3(82)
1 State-Space Linear Systems
5(7)
1.1 State-Space Linear Systems
5(2)
1.2 Block Diagrams
7(4)
1.3 Exercises
11(1)
2 Linearization
12(19)
2.1 State-Space Nonlinear Systems
12(1)
2.2 Local Linearization Around an Equilibrium Point
12(3)
2.3 Local Linearization Around a Trajectory
15(1)
2.4 Feedback Linearization
16(6)
2.5 Practice Exercises
22(5)
2.6 Exercises
27(4)
3 Causality, Time Invariance, And Linearity
31(12)
3.1 Basic Properties of LTV/LTI Systems
31(2)
3.2 Characterization of All Outputs to a Given Input
33(1)
3.3 Impulse Response
34(3)
3.4 Laplace and Z Transforms (Review)
37(1)
3.5 Transfer Function
38(1)
3.6 Discrete-Time Case
39(1)
3.7 Additional Notes
40(2)
3.8 Exercises
42(1)
4 Impulse Response And Transfer Function Of State-Space Systems
43(13)
4.1 Impulse Response and Transfer Function for LTI Systems
43(1)
4.2 Discrete-Time Case
44(1)
4.3 Elementary Realization Theory
45(4)
4.4 Equivalent State-Space Systems
49(1)
4.5 LTI Systems in MATLAB®
50(2)
4.6 Practice Exercises
52(1)
4.7 Exercises
53(3)
5 Solutions To LTV Systems
56(8)
5.1 Solution to Homogewous Linear Systems
56(2)
5.2 Solution to Nonhomogeneous Linear Systems
58(1)
5.3 Discrete-Time Case
59(2)
5.4 Practice Exercises
61(1)
5.5 Exercises
62(2)
6 Solutions To LTI Systems
64(12)
6.1 Matrix Exponential
64(1)
6.2 Properties of the Matrix Exponential
65(2)
6.3 Computation of Matrix Exponentials Using Laplace Transforms
67(1)
6.4 The Importance of the Characteristic Polynomial
68(1)
6.5 Discrete-Time Case
69(1)
6.6 Symbolic Computations in MATLAB®
70(2)
6.7 Practice Exercises
72(2)
6.8 Exercises
74(2)
7 Solutions To LTI Systems: The Jordan Normal Form
76(9)
7.1 Jordan Normal Form
76(2)
7.2 Computation of Matrix Powers using the Jordan Normal Form
78(2)
7.3 Computation of Matrix Exponentials using the Jordan Normal Form
80(1)
7.4 Eigenvalues with Multiplicity Larger than 1
81(1)
7.5 Practice Exercise
82(1)
7.6 Exercises
83(2)
II Stability
85(42)
8 Internal Or LYAPUNOV Stability
87(21)
8.1 Lyapunov Stability
87(1)
8.2 Vector and Matrix Norms (Review)
88(2)
8.3 Eigenvalue Conditions for Lyapunov Stability
90(1)
8.4 Positive-Definite Matrices (Review)
91(1)
8.5 Lyapunov Stability Theorem
91(4)
8.6 Discrete-Time Case
95(3)
8.7 Stability of Locally Linearized Systems
98(5)
8.8 Stability Tests with MATLAB®
103(1)
8.9 Practice Exercises
103(2)
8.10 Exercises
105(3)
9 Input-Output Stability
108(12)
9.1 Bounded-Input, Bounded-Output Stability
108(1)
9.2 Time Domain Conditions for BIBO Stability
109(3)
9.3 Frequency Domain Conditions for BIBO Stability
112(1)
9.4 BIBO versus Lyapunov Stability
113(1)
9.5 Discrete-Time Case
114(1)
9.6 Practice Exercises
115(3)
9.7 Exercises
118(2)
10 Preview Of Optimal Control
120(7)
10.1 The Linear Quadratic Regulator Problem
120(1)
10.2 Feedback Invariants
121(1)
10.3 Feedback Invariants in Optimal Control
122(1)
10.4 Optimal State Feedback
122(2)
10.5 LQR with MATLAB®
124(1)
10.6 Practice Exercise
124(1)
10.7 Exercise
125(2)
III Controllability And State Feedback
127(50)
11 Controllable And Reachable Subspaces
129(19)
11.1 Controllable and Reachable Subspaces
129(1)
11.2 Physical Examples and System Interconnections
130(4)
11.3 Fundamental Theorem of Linear Equations (Review)
134(1)
11.4 Reachability and Controllability Gramians
135(2)
11.5 Open-Loop Minimum-Energy Control
137(1)
11.6 Controllability Matrix (LTI)
138(3)
11.7 Discrete-Time Case
141(4)
11.8 MATLAB® Commands
145(1)
11.9 Practice Exercise
146(1)
11.10 Exercises
147(1)
12 Controllable Systems
148(14)
12.1 Controllable Systems
148(2)
12.2 Eigenvector Test for Controllability
150(2)
12.3 Lyapunov Test for Controllability
152(3)
12.4 Feedback Stabilization Based on the Lyapunov Test
155(1)
12.5 Eigenvalue Assignment
156(1)
12.6 Practice Exercises
157(2)
12.7 Exercises
159(3)
13 Controllable Decompositions
162(6)
13.1 Invariance with Respect to Similarity Transformations
162(1)
13.2 Controllable Decomposition
163(2)
13.3 Block Diagram Interpretation
165(1)
13.4 Transfer Function
166(1)
13.5 MATLAB® Commands
166(1)
13.6 Exercise
167(1)
14 Stabilizability
168(9)
14.1 Stabilizable System
168(1)
14.2 Eigenvector Test for Stabilizability
169(2)
14.3 Popov-Belevitch-Hautus (PBH) Test for Stabilizability
171(1)
14.4 Lyapunov Test for Stabilizability
171(2)
14.5 Feedback Stabilization Based on the Lyapunov Test
173(1)
14.6 MATLAB® Commands
174(1)
14.7 Exercises
174(3)
IV Observability And Output Feedback
177(44)
15 Observability
179(19)
15.1 Motivation: Output Feedback
179(1)
15.2 Unobservable Subspace
180(2)
15.3 Unconstructible Subspace
182(1)
15.4 Physical Examples
182(2)
15.5 Observability and Constructibility Gramians
184(1)
15.6 Gramian-Based Reconstruction
185(2)
15.7 Discrete-Time Case
187(1)
15.8 Duality for LTI Systems
188(2)
15.9 Observability Tests
190(3)
15.10 MATLAB® Commands
193(1)
15.11 Practice Exercises
193(2)
15.12 Exercises
195(3)
16 Output Feedback
198(12)
16.1 Observable Decomposition
198(2)
16.2 Kalman Decomposition Theorem
200(2)
16.3 Detectability
202(2)
16.4 Detectability Tests
204(1)
16.5 State Estimation
205(1)
16.6 Eigenvalue Assignment by Output Injection
206(1)
16.7 Stabilization through Output Feedback
207(1)
16.8 MATLAB® Commands
208(1)
16.9 Exercises
208(2)
17 Minimal Realizations
210(13)
17.1 Minimal Realizations
210(1)
17.2 Markov Parameters
211(2)
17.3 Similarity of Minimal Realizations
213(2)
17.4 Order of a Minimal SISO Realization
215(2)
17.5 MATLAB® Commands
217(1)
17.6 Practice Exercises
217(2)
17.7 Exercises
219(2)
Linear Systems II Advanced Material 221(104)
V Poles And Zeros Of Mimo Systems
223(28)
18 Smith-McMillan Form
225(10)
18.1 Informal Definition of Poles and Zeros
225(1)
18.2 Polynomial Matrices: Smith Form
226(3)
18.3 Rational Matrices: Smith-McMillan Form
229(1)
18.4 McMillan Degree, Poles, and Zeros
230(2)
18.5 Blocking Property of Transmission Zeros
232(1)
18.6 MATLAB® Commands
233(1)
18.7 Exercises
233(2)
19 State-Space Poles, Zeros, And Minimality
235(9)
19.1 Poles of Transfer Functions versus Eigenvalues of State-Space Realizations
235(1)
19.2 Transmission Zeros of Transfer Functions versus Invariant Zeros of State-Space Realizations
236(3)
19.3 Order of Minimal Realizations
239(2)
19.4 Practice Exercises
241(1)
19.5 Exercise
242(2)
20 System Inverses
244(7)
20.1 System Inverse
244(1)
20.2 Existence of an Inverse
245(1)
20.3 Poles and Zeros of an Inverse
246(2)
20.4 Feedback Control of Invertible Stable Systems with Stable Inverses
248(1)
20.5 MATLAB® Commands
249(1)
20.6 Exercises
250(1)
VI LQR/LQG Optimal Control
251(74)
21 Linear Quadratic Regulation (LQR)
253(7)
21.1 Deterministic Linear Quadratic Regulation (LQR)
253(1)
21.2 Optimal Regulation
254(1)
21.3 Feedback Invariants
255(1)
21.4 Feedback Invariants in Optimal Control
256(1)
21.5 Optimal State Feedback
256(2)
21.6 LQR in MATLAB®
258(1)
21.7 Additional Notes
258(1)
21.8 Exercises
259(1)
22 The Algebraic Riccati Equation (ARE)
260(8)
22.1 The Hamiltonian Matrix
260(1)
22.2 Domain of the Riccati Operator
261(1)
22.3 Stable Subspaces
262(1)
22.4 Stable Subspace of the Hamiltonian Matrix
262(4)
22.5 Exercises
266(2)
23 Frequency Domain And Asymptotic Properties Of LQR
268(21)
23.1 Kalman's Equality
268(2)
23.2 Frequency Domain Properties: Single-Input Case
270(2)
23.3 Loop Shaping Using LQR: Single-Input Case
272(3)
23.4 LQR Design Example
275(3)
23.5 Cheap Control Case
278(3)
23.6 MATLAB® Commands
281(1)
23.7 Additional Notes
282(1)
23.8 The Loop-Shaping Design Method (Review)
283(5)
23.9 Exercises
288(1)
24 Output Feedback
289(16)
24.1 Certainty Equivalence
289(1)
24.2 Deterministic Minimum-Energy Estimation (MEE)
290(5)
24.3 Stochastic Linear Quadratic Gaussian (LQG) Estimation
295(1)
24.4 LQR/LQG Output Feedback
295(1)
24.5 Loop Transfer Recovery (LTR)
296(1)
24.6 Optimal Set-Point Control
297(5)
24.7 LQR/LQG with MATLAB®
302(1)
24.8 LTR Design Example
303(1)
24.9 Exercises
304(1)
25 LQG/LQR And The Q Parameterization
305(5)
25.1 Q-Augmented LQG/LQR Controller
305(1)
25.2 Properties
306(3)
25.3 Q Parameterization
309(1)
25.4 Exercise
309(1)
26 Q DESIGN
310(15)
26.1 Control Specifications for Q Design
310(3)
26.2 The Q Design Feasibility Problem
313(1)
26.3 Finite-Dimensional Optimization: Ritz Approximation
314(2)
26.4 Q Design Using MATLAB® and CVX
316(5)
26.5 Q Design Example
321(2)
26.6 Exercise
323(2)
Bibliography 325(2)
Index 327
João P. Hespanha is professor of electrical engineering in the Center for Control, Dynamical Systems and Computation at the University of California, Santa Barbara. He is the author of Noncooperative Game Theory (Princeton).