PID trajectory tracking control for mechanical systems

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Edition: 1

Series: Lecture notes in control and information sciences 298

ISBN: 3540205675, 9783540205678

Size: 5 MB (4947345 bytes)

Pages: 116/116

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Youngjin Choi, Wan Kyun Chung3540205675, 9783540205678

The strength of PID control lies in its simplicity, lucid meaning, and clear effect. Although PID control is a widely accepted method for controlling mechanical systems it is hard to find a book on PID control for mechanical systems. This monograph discusses thoroughly the theoretical bases, e.g., optimality of PID control, performance tuning rules, automatic performance tuning method, and output feedback PID control for mechanical control systems – clearly presenting the characteristics and theory of mechanical control systems.

Table of contents :
1.1 Motivation……Page 17
1.2 Historic PD and PID……Page 18
1.3 Book Preview……Page 19
1.4 Notations……Page 21
2.1 Introduction……Page 22
2.2 Nonlinear Mechanical Control Systems……Page 23
2.2.1 Lagrangian System……Page 24
2.2.2 Hamiltonian System……Page 25
2.3.1 Global Asymptotic Stability……Page 26
2.3.2 Direct H ” Control……Page 28
2.4.1 Optimal Control of a Modified-CTC……Page 31
2.4.2 H Control of a Modified-CTC……Page 35
2.5 Notes……Page 39
3.1 Introduction……Page 40
3.2 State-Space Description of Lagrangian Systems……Page 41
3.3.1 ISS-CLF for Lagrangian Systems……Page 43
3.3.2 H Optimality of PID Control Law……Page 46
3.4 Inverse Optimal PID Control……Page 49
3.4.1 Selction Guidelines for Gains……Page 51
3.4.2 Performance Estimation by Optimality……Page 53
3.4.3 Illustrative Example……Page 54
3.5 Summary……Page 57
4.1 Introduction……Page 58
4.2.1 Performance Limitation for State Vector……Page 59
4.2.2 Square and Linear Rules……Page 64
4.2.3 Illustrative Example……Page 65
4.3 Compound Performance Tuning……Page 67
4.3.1 Performance Limitation for Composite Error……Page 68
4.3.2 Compound Rule……Page 70
4.3.3 Illustrative Example……Page 71
4.4 Experimental Results……Page 72
4.4.1 Experiment: Square and Linear Rules……Page 73
4.4.2 Experiment: Performance Estimation by Optimality……Page 77
4.4.3 Experiment: Compound Rule……Page 78
4.5 Summary……Page 80
5.1 Introduction……Page 82
5.2 Quasi-equilibrium Region……Page 83
5.3 Automatic Performance Tuning……Page 86
5.3.1 Auto-tuning Law……Page 87
5.3.2 Criterion for Auto-tuning……Page 89
5.3.3 Performance Enhanced by Auto-tuning Law……Page 90
5.4 Model Adaptation……Page 92
5.5 Experimental Results……Page 94
5.6 Summary……Page 96
6.1 Introduction……Page 97
6.2 Normal Form of Langranian Systems……Page 98
6.3.1 Observer Gain……Page 99
6.3.2 Stability……Page 101
6.3.3 Reduced-Order ID State Observer……Page 106
6.4 Notes……Page 108

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