[按需印刷] 事件触发自抗扰控制:理论与应用(英文版)

事件触发采样控制方法近期受到学术界和工业界的广泛关注并迅速发展。本书内容属于控制科学与工程学科，是系统阐述事件触发自抗扰控制器设计方法的第一本专著。本书聚焦在理论研究和工业应用中均备受关注的自抗扰控制方法，着重探讨事件触发自抗扰控制器的系统化设计问题，通过多个具体应用实例展示事件触发自抗扰控制方法在工程系统中的实现和得到的实际效果。本书为事件触发采样控制理论研究提供新的发展方向，也为控制工程师提供利用有限采样信息得到满意控制性能的有效方法。特别的，自抗扰控制由韩京清教授于上世纪九十年代提出，是为数不多的由我国学者自主提出并得到成功应用的控制方法；本书以自抗扰控制为基本方法探讨事件触发采样控制这


Contents
1 Introduction 1
1.1 Event-Based Sampled-Data Control 1
1.1.1 Sampled-Data Systems 2
1.1.2 Event-Based Sampling and Control 4
1.2 Active Disturbance Rejection Control 6
1.2.1 Functions f han and f al 7
1.2.2 Tracking Differentiator 8
1.2.3 Extended State Observer 9
1.2.4 Nonlinear Feedback 10
1.3 Related Literature 11
1.3.1 Event-Based Sampled-Data Control 11
1.3.2 Active Disturbance Rejection Control 18
1.3.3 Event-Based Active Disturbance Rejection Control 21
1.4 Organization of the Book 22
References 23
Part I Theoretic Developments
2 Performance Assessment of Discrete-Time Extended StateObservers 31
2.1 Problem Formulation 31
2.1.1 Discrete-Time Nonlinear System 31
2.1.2 Discrete-Time Extended State Observer 33
2.1.3 Description of the Problem 34
2.2 Observation Performance Analysis of Discrete-Time Extended State Observer 34
2.2.1 Gain Parameters Design Based on Spectral Radius Method 34
2.2.2 Observation Performance Analysis Through Ellipsoidal Set Approach 36
2.2.3 Extensions and Special Cases 46
2.3 Numerical Example 50
2.4 Experimental Results 53
2.5 Summary 58
References 58
3 Event-Triggered Extended State Observer 61
3.1 Problem Formulation 61
3.1.1 Continuous-Time Nonlinear System 61
3.1.2 Event-Triggered Extended State Observer 63
3.1.3 ET-ESO Design Problem 64
3.2 Main Theoretic Results 64
3.2.1 Event-Triggering Condition Design 65
3.2.2 Non-existence of Zeno Phenomenon 65
3.2.3 Convergence Analysis of Event-Triggered Extended State Observer 67
3.2.4 Other Extensions 71
3.2.5 Event-Triggered Extended State Observer with Designed Initial Value 72
3.3 Numerical Example 73
3.3.1 Observation Performance Verification for ET-ESO 76
3.4 Summary 78
References 78
4 Event-Triggered Active Disturbance Rejection Control 81
4.1 Problem Description 81
4.2 Event-Triggered Control Based on Continuous-Time Observations 83
4.3 Separate Event-Triggered Observation and Control 91
4.4 Experimental Results 96
4.5 Summary 102
References 102
5 A High-Gain Approach to Event-Triggered Control 105
5.1 Problem Formulation 106
5.2 Theoretic Results 110
5.3 Discussions on Special Sampling Schemes 117
5.3.1 Case 1:Only Sampling Output 117
5.3.2 Case 2:Only Sampling Control Signal 122
5.4 Numerical Example 126
5.5 Experimental Performance Evaluation 128
5.6 Summary 134
References 134
6 Event-Triggered Active Disturbance Rejection Control of DC Torque Motors 137
6.1 Background 137
6.2 Problem Description and System Dynamics 139
6.3 Event-Triggered ADRC Design 144
6.4 Experimental Performance Evaluation 149
6.4.1 Experimental Results with Squarewave-Type Input 150
6.4.2 Experimental Results with Multitone Sinusoid Input 154
6.5 Summary 157
References 157
7 Event-Triggered ADRC for Electric Cylinders with PD-Type Event-Triggering Conditions 161
7.1 Background 161
7.2 Nonlinear Modeling and Problem Formulation 163
7.3 Event-Triggered ADRC of Electric Cylinders 168
7.4 Experiment Results 175
7.4.1 Squarewave-Type Reference 177
7.4.2 Multitone Sinusoid Reference 179
7.5 Discussion 181
References 181
8 Event-Triggered Attitude Tracking for Rigid Spacecraft 183
8.1 Background 183
8.2 Problem Formulation 184
8.3 ET-ADRC Design 190
8.4 Numerical Evaluation 195
8.4.1 Desired Angular Velocity in Sinusoidal Form 196
8.4.2 Desired Angular Velocity in Square Wave Form 200
8.5 Summary 201
References 203
9 Event-Triggered Adaptive Disturbance Rejection for Artificial
Pancreas 205
9.1 Background 205
9.2 Related Literature 206
9.3 Controller Structure Design 207
9.3.1 Time-Optimal Control Synthesis Function 208
9.3.2 Tracking Differentiator 209
9.3.3 Extended State Observer 210
9.3.4 Nonlinear Feedback 210
9.3.5 Safety Constraints 211
9.3.6 Pump-Discretization 211
9.4 Event-Triggered Parameter Adaptation for ADRC 212
9.4.1 Adaptation of ESO and IOB 212
9.4.2 Parameter Adaptation for Nonlinear Feedback 213
9.4.3 Parameter Design 216
9.5 In Silico Performance Analysis 216
9.5.1 Announced Meals with Nominal Basal Rate 217
9.5.2 Unannounced Meals with Nominal Basal Rate 219
9.5.3 Robust Performance Evaluation 220
9.6 Summary 221
References 223
10 Summary and Future Work 227
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