Modern Control System TheoryAbout the book... The book provides an integrated treatment of continuous-time and discrete-time systems for two courses at postgraduate level, or one course at undergraduate and one course at postgraduate level. It covers mainly two areas of modern control theory, namely; system theory, and multivariable and optimal control. The coverage of the former is quite exhaustive while that of latter is adequate with significant provision of the necessary topics that enables a research student to comprehend various technical papers. The stress is on interdisciplinary nature of the subject. Practical control problems from various engineering disciplines have been drawn to illustrate the potential concepts. Most of the theoretical results have been presented in a manner suitable for digital computer programming along with the necessary algorithms for numerical computations. |
Contents
Introduction | 1 |
Linear Spaces and Linear Operators | 10 |
State Variable Descriptions | 64 |
Physical Systems and State Assignment | 99 |
Solution of State Equations | 146 |
Controllability and Observability | 200 |
MinimumEnery Control | 208 |
Observability Tests for ContinuousTime Systems | 217 |
Stability | 312 |
Model Control | 372 |
General Mathematical Procedures | 418 |
Optimal Feedback Control | 497 |
Stochastic Optimal Linear Estimation and Control | 590 |
Theorems and Pairs | 627 |
Answers and Aids to Problems | 641 |
| 681 | |
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Common terms and phrases
algorithm assume asymptotically stable Ax(t b₁ B₂ boundary conditions Bu(t canonical form Cayley-Hamilton theorem Chapter characteristic polynomial closed-loop system CN+1 coefficients column companion form Consider constant matrix constraints continuous-time systems control system control theory controllable and observable defined determine diagram differential equation discrete-time discrete-time systems dynamic eigenvalues eigenvectors estimation Example feedback control finite given by eqn Gu(k IEEE Trans initial conditions input integral k₁ Kalman linear regulator linear system linear time-invariant system linearly independent Lyapunov function m₁ method minimizes n-dimensional nonlinear obtain optimal control optimal control law output performance index plant positive definite real numbers refer eqn regulator problem result Riccati equation rows sampling satisfies scalar Section shown in Fig solution solve stability steady-state subspace symmetric t₁ Theorem time-varying trajectory transfer function transformation transition matrix unique variables vector space x₁ zero дх