Using the tools of optimal, robust and adaptive control, the authors develop the theory and practice of high performance control in a real world environment. The book presupposes standard knowledge of linear algebra, probability theory, linear dynamical systems and control theory.
Author(s): Teng-Tiow Tay
Series: Progress in Mathematics
Publisher: Birkhauser
Year: 1998
Language: English
Pages: 362
Tags: Автоматизация;Теория автоматического управления (ТАУ);Книги на иностранных языках;
Title Page......Page 1
Preface......Page 3
Contents......Page 7
List of Figures......Page 11
List of Tables......Page 15
1.1 Introduction......Page 17
1.2 Beyond Classical Control......Page 19
1.3 Robustness and Performance......Page 22
1.5 Book Outline......Page 30
1.7 Main Points of Chapter......Page 32
1.8 Notes and References......Page 33
2.1 Introduction......Page 35
2.2 The Nominal Plant Model......Page 36
2.3 The Stabilizing Controller......Page 44
2.4 Coprime Factorization......Page 50
2.5 All Stabilizing Feedback Controllers......Page 57
2.6 All Stabilizing Regulators......Page 67
2.7 Notes and References......Page 68
3.2 Signals and Disturbances......Page 75
3.3 Plant Uncertainties......Page 80
3.4 Plants Stabilized by a Controller......Page 84
3.5 State Space Representation......Page 97
3.6 Notes and References......Page 105
4.1 Introduction......Page 107
4.2 Selection of Performance Index......Page 108
4.3 An LQG/LTR Design......Page 116
4.4 H-infinity Optimal Design......Page 127
4.5 An l1 Design Approach......Page 131
4.6 Notes and References......Page 142
5.1 Introduction......Page 143
5.2 Iterated (Q,S) Design......Page 145
5.3 Nested (Q,S) Design......Page 161
5.4 Notes and References......Page 171
6.1 Introduction......Page 173
6.2 Q-Augmented Controller Structure: Ideal Model
Case......Page 174
6.3 Adaptive-Q Algorithm......Page 176
6.4 Analysis of the Adaptive-Q Algorithm: Ideal Case......Page 178
6.5 Q-augmented Controller Structure: Plant-model Mismatch......Page 182
6.6 Adaptive Algorithm......Page 185
6.7 Analysis of the Adaptive-Q Algorithm:
Unmodeled Dynamics Situation......Page 187
6.8 Notes and References......Page 192
7.1 Introduction......Page 195
7.2 System Description and Control Problem Formulation......Page 196
7.3 Adaptive Algorithms......Page 201
7.4 Adaptive Algorithm Analysis: Ideal case......Page 203
7.5 Adaptive Algorithm Analysis: Nonideal Case......Page 211
7.6 Notes and References......Page 220
8.1 Introduction......Page 223
8.2 Adaptive-Q Method for Nonlinear Control......Page 224
8.3 Stability Properties......Page 235
8.4 Learning-Q Schemes......Page 247
8.5 Notes and References......Page 258
9.1 Introduction......Page 259
9.2 Algorithms for Continuous-time Plant......Page 261
9.3 Hardware Platform......Page 262
9.4 Software Platform......Page 280
9.5 Other Issues......Page 284
9.6 Notes and References......Page 286
10.2 Control of Hard-disk Drives......Page 287
10.3 Control of a Heat Exchanger......Page 295
10.4 Aerospace Resonance Suppression......Page 305
A.1 Matrices and Vectors......Page 313
A.3 Determinant and Rank of a Matrix......Page 314
A.5 Eigenvalues, Eigenvectors and Trace......Page 315
A.7 Positive Definite Matrices and Matrix Decompositions......Page 316
A.8 Norms of Vectors and Matrices......Page 317
A.10 Lemma of Lyapunov......Page 318
A.12 Basis and Dimension......Page 319
A.13 Mappings and Linear Mappings......Page 320
B.1 Linear Dynamical Systems......Page 321
B.2 Norms, Spaces and Stability Concepts......Page 325
B.3 Nonlinear Systems Stability......Page 326
C.2 Averaging......Page 329
C.3 Transforming an adaptive system into standard form......Page 336
C.4 Averaging Approximation......Page 339
References......Page 341
Author Index......Page 349
Subject Index......Page 353
