Couples control engineering with modern development in science via the concept of entropy. Control activity is explained based on the principles that control is making a system do what we want it to do, relating control theory with the sciences.
Author(s): George N. Saridis
Series: Series in Intelligent Control and Intelligent Automation v. 12
Publisher: World Scientific Publishing Company
Year: 2001
Language: English
Pages: 148
Tags: Автоматизация;Теория автоматического управления (ТАУ);Книги на иностранных языках;
Contents ......Page 8
Table Of Figures ......Page 11
Preface ......Page 12
1.1 Introduction: ......Page 14
1.2.1 Review Of Entropy Concepts ......Page 16
1.2.2 Entropy And Thermodynamics ......Page 17
1.2.3 Entropy And Information Theory ......Page 18
1.2.6 The Principle Of Increasing Precision Decreasing Intelligence ......Page 19
1.3 Uncertainty And The Control Problem ......Page 20
1.5 Automatic Control Systems ......Page 21
1.6 Entropy Formulation Of Control ......Page 23
1.7 Conclusions ......Page 25
1.8 References ......Page 26
2.2 The Deterministic Optimal Control ......Page 29
2.3 The Stochastic Optimal Control Problem ......Page 30
2.4 The Stochastic Suboptimal Control Problem ......Page 32
2.5 Discrete-Time Formulation Of The Stochastic Optimal Control Problem ......Page 33
2.6 Maximum Entropy Formulation Of State Estimation: Continuous-Time ......Page 35
2.7 Maximum Entropy Formulation Of State Estimation: Discrete-Time ......Page 37
2.8 The Cost Of Active Feedback (Dual) Control Problem ......Page 39
2.9 Stochastic Optimal (Dual) Estimation And Control ......Page 41
2.11 Stochastic Optimal Adaptive Control ......Page 42
2.11.1 Example: The Dual-Optimal And Adaptive Control ......Page 43
2.12 The LQG Optimal Control And The Kalman-Bucy Filter......Page 48
2.13 Upper Bound Of The Equivocation H[o/u*]......Page 50
2.13.1 Example: The Upper Bound Of Equivocation ......Page 51
2.15 References ......Page 55
3.1.1 Derivation Of The IDI......Page 58
3.2.1 The Architecture ......Page 61
3.2.2 The Analytic Model ......Page 62
3.3.1 The Architecture ......Page 65
3.3.2 The Analytic Model ......Page 69
3.4.1 The System And The Architecture ......Page 75
3.4.2 Entropy Formulation Of Motion Control ......Page 76
3.4.3 Entropy Measure Of The Vision System ......Page 79
3.5 Conclusions ......Page 80
3.6 References ......Page 81
4.2 Definition Of Reliability ......Page 83
4.3 Reliability Measures ......Page 84
4.4 Entropy Measures Of Reliability ......Page 85
4.5 The Looser Lower Bound ......Page 87
4.6 Reliability-Based Intelligent Control ......Page 90
4.7 Illustrative Example ......Page 91
4.9 References ......Page 94
5.1 Automation ......Page 95
5.2 Intelligent Manufacturing ......Page 96
5.3.1 Product Scheduling Architecture: The Organization Level ......Page 101
5.3.2 Product Scheduling Architecture: The Coordination Level ......Page 104
5.4.1 The Organization Level Structure ......Page 108
5.4.2 The Coordination Level Structure ......Page 110
5.6 Conclusions ......Page 111
5.7 References ......Page 114
6.2 The Environmental Systems ......Page 115
6.3 Ecological Systems ......Page 117
6.4 Biochemical Systems ......Page 118
6.7 Econometric Models ......Page 119
6.8 The Optimal Control For Global Entropy ......Page 120
6.9 Conclusions ......Page 121
6.10 References ......Page 122
7.1 Introduction ......Page 123
7.3 The Architecture Of The Coordination Level ......Page 125
7.4 The Analytic Model ......Page 127
7.5 The Architecture Of The Execution Level ......Page 130
7.6 Entropy Formulation Of Motion Control ......Page 133
7.7 Entropy Measure Of The Vision System ......Page 135
7.8 Entropy Measure For The Sensory System ......Page 136
7.11 References ......Page 137
8.2 Irreversibility Of Processes ......Page 140
8.4 Entropy And Control Engineering And Chaos ......Page 141
8.5 Remarks ......Page 142
8.6 References ......Page 143
Index ......Page 145
