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PART 1 1

1 Introduction and Linearized Dynamic Models 1

1.1 Introduction 1

1.2 Examples and Classifications of Control Systems 1

1.3 Open-Loop Control and Closed-Loop Control 3

1.4 Control System Analysis and Design 6

1.5 Linearized Dynamic Models 8

1.6 Laplace Transforms 11

1.7 Transfer Functions and System Response 15

1.8 Block Diagram Reduction 20

1.9 Conclusion 24

2 Transfer Function Models of Physical Systems 29

2.1 Introduction 29

2.2 Mechanical Systems 29

2.3 Electrical Systems：Circuits 34

2.4 Electromechanical Systems：Transfer Functions of Motors and Generators 39

2.5 Thermal Systems 43

2.6 Fluid Systems 47

2.7 Fluid Power Control Elements 54

2.8 Conclusion 58

3 Transient Performance and the S-Plane 65

3.1 Introduction 65

3.2 The S-Plane，Pole-Zero Patterns，and Residue Calculation 65

3.3 Transient Response，Including Repeated and Complex Poles 69

3.4 Simple Lag：First-Order Systems 76

3.5 Quadratic Lag：Second-Order Systems 78

3.6 Performance and Stability of Higher-Order Systems 85

3.7 Routh-Hurwitz Stability Criterion 88

3.8 Effect of System Zeros 92

3.9 Conclusion 99

4 Feedback System Modeling and Performance 104

4.1 Introduction 104

4.2 Feedback System Model Examples 104

4.3 Direct Block Diagram Modeling of Feedback Systems 108

4.4 Effect of Feedback on Parameter Sensitivity and Disturbance Response 111

4.5 Steady-State Errors in Feedback Systems 117

4.6 Transient Response versus Steady-State Errors 120

4.7 Conclusion 125

PART 2 130

1 Robustness in Multivariable Control System Design 130

1.1 Introduction 130

1.2 Sensitivity of the Characteristic Gain Loci 132

1.3 Uncertainty in a Feedback System 135

1.4 Relative Stability Matrices 137

1.5 Multivariable Gain and Phase Margins 139

1.6 Conclusion 144

2 The Inverse Nyquist Array Design Method 148

2.1 Introduction 148

2.2 The Multivariable Design Problem 149

2.3 Stability 152

2.4 Design Technique 158

2.5 Conclusion 162

3 Optimal Control 166

3.1 The Calculus of Variations：Classical Theory 166

3.2 The Optimal Control Problem 168

3.3 Singular Control Problems 172

3.4 Dynamic Programming 176

3.5 The Hamilton-Jacobi Approach 178

4 Optimisation in Multivariable Design 184

4.1 Introduction 184

4.2 Problem Formulation 185

4.3 Allocation Problem 188

4.4 Scaling Problem 190

4.5 Compensator Design 192

4.6 Design Example 194

4.7 Discussion 196

5 Pole Assignment 200

5.1 Introduction 200

5.2 State-Feedback Algorithms 201

5.3 Output-Feedback Algorithms 208

5.4 Concluding Remarks 216

PART 3 221

1 Multivariable Frequency Domain Design Method for Disturbance Minimization 221

1.1 Introduction 221

1.2 Statement of the Problem 222

1.3 Design Scheme for Disturbance Minimization 223

1.4 Illustrative Example 228

1.5 Conclusion 230

2 Application of the Robust Servomechanism Controller to Systems with Periodic Tracking Disturbance Signals 237

2.1 Introduction 237

2.2 Development 239

2.3 Numerical Examples 244

2.4 Conclusion 248

3 Regulator Design with Poles in a Specified Region 253

3.1 Introduction 253

3.2 Preliminaries 254

3.3 Pole Assignment in a Specified Region 258

3.4 Optimal Regulator with its Poles in a Specified Region 264

3.5 Conclusion 272

4 Direct Adaptive Output Tracking Control Using Multilayered Neural Networks 275

4.1 Introduction 275

4.2 Nonlinear Control Formulation 276

4.3 Adaptive Tracking Using Multilayered Neural Networks 279

4.4 Results on Convergence of Weight Learning 283

4.5 Results on Feedback Stability 284

4.6 Simulation Results 289

4.7 Concluding Remarks 289

5 Genetic Algorithms-A Robust Optimization Tool 294

5.1 Introduction 294

5.2 Genetic Algorithms 295

5.3 GA in Aerospace System Optimization 305

5.4 Summary and Discussion 307