1. 1 PID control principle 1
Analog PID simulation of 1.2 continuous system Ⅱ
1.2. 1 basic PID control2
1.2.2 PID control of linear time-varying system 8
1.3 digital PID control 12
1.3. 1 position PID control algorithm 12
Simulation of digital PID control for 1.3.2 continuous system
Simulation of digital PID control for 1.3.3 discrete system
1.3.4 incremental PID control algorithm and simulation 25
1.3.5 integral separation PID control algorithm and simulation 27
1.3.6 anti-integral saturation PID control algorithm and simulation 32
1.3.7 trapezoidal integral PID control algorithm 35
1.3.8 variable speed integral PID algorithm and simulation 35
1.3.9 PID control simulation with filter 39
1.3. 10 incomplete differential PID control algorithm and simulation 45
1.3. 1 1 differential lead PID control algorithm and simulation 49
1.3. 12 PID control algorithm with dead zone and its simulation 52
1.3. 13 PID control algorithm based on feedforward compensation and its simulation 56
1.3. 14-step PID control algorithm and simulation 59
1.3.15 square wave response controlled by PID 6 1
1.3. 16 PID control based on Kalman filter 64
1.4 S function introduction 73
1.4. 1 S function introduction 73
1.4.2 S function uses step 73.
Basic functions and important parameter settings of 1.4.3 S function 73
1.4.4 Example Description 74
New progress of 1.5 PID research 74
Chapter 2 Settings of PID Controller 76
2. 1 overview 76
2.2 PID adjustment based on response curve method 76
2.2. 1 basic principles
2.2.2 Simulation example 77
2.3 frequency domain response PID adjustment based on Ziegler-Nichols 8 1
2.3. 1 PID tuning of continuous Ziegler-Nichols method
2.3.2 Simulation Example 8 1
2.3.3 PID adjustment of discrete Ziegler-Nichols method 84
2.3.4 Simulation example 84
2.4 PD setting based on frequency domain analysis 88
2.4. 1 basic principles
2.4.2 Simulation example 88
2.5 PI control based on phase margin tuning 9 1
Basic principle 9 1
2.5.2 Simulation example 94
2.6 Stable PD Control Based on Pole Assignment 95
2.6. 1 basic principles
2.6.2 Simulation example 96
2.7 PID adjustment based on critical proportional band method 98
Basic principle 98
2.7.2 Simulation example 99
2.8 a kind of nonlinear tuning PID control 10 1
Basic principles 10 1
2.8.2 Simulation example 103
2.9 PID tuning based on optimization function 105
2.9. 1 basic principles 105
2.9.2 Simulation example 105
2. 10 PID tuning based on NCD optimization 107
2. 10. 1 basic principle 107
2. 10.2 simulation example 107
2. 1 1 PID tuning based on NCD and optimization function
Basic principles 1 1. 1
2. 1 1.2 Simulation example11
2. 12 Frequency domain test of transfer function 1 13
2. 12. 1 basic principle 1 13
2. 12.2 Simulation example 1 14
Chapter 3 PID control of time-delay system 1 17
3. 1 single loop PID control system 1 17
3.2 cascade PID control 1 17
3.2. 1 cascade PID control principle 1 17
3.2.2 Simulation example 1 18
3.3 Dalin control algorithm for pure time-delay systems 122
3.3. 1 principle of dalin control algorithm 122
3.3.2 Simulation example 122
3.4 Smith control algorithm for time-delay systems 124
3.4. 1 continuous Smith predictive control
3.4.2 Simulation example 126
3.4.3 Digital Smith Predictive Control 128
3.4.4 Simulation example 129
Chapter 4 PID control based on differentiator 134.
4. 1 PID control based on full-range fast differentiator 134
4. 1. 1 full range fast differentiator 134
4. 1.2 Simulation example 134
4.2 PID control based on Levant differentiator 143
4.2. 1 Levant differentiator 143
4.2.2 Simulation example 144
Chapter 5 PID control based on observer 156.
5. 1 PID control based on slow disturbance observer compensation
5. 1. 1 system description 156
5. 1.2 observer design 156
5. 1.3 Simulation example 157
5.2 PID control based on disturbance observer 162
5.2. 1 Basic principle of interference observer 162
5.2.2 Performance Analysis of Interference Observer 164
5.2.3 Robust stability of disturbance observer 166
5.2.4 Design of low-pass filter 167
5.2.5 Simulation example 168
5.3 PID control based on extended observer 172
5.3. Design of1extended observer 172
5.3.2 Analysis of Extended Observer 173
5.3.3 Simulation example 175
5.4 PID control based on output delay observer 189
System description 189
5.4.2 Design of Output Delay Observer 189
5.4.3 Analysis of Delay Observer 190
5.4.4 Simulation example 19 1
Chapter 6 ADRC and its PID control 20 1
6. 1 nonlinear tracking differentiator 20 1
6. 1. 1 differentiator description 20 1
6. 1.2 Simulation Example 20 1
6.2 Arrangement of Transition Process and PID Control 205
6.2. 1 Arrange the transition process 205
6.2.2 Simulation Example 206
6.3 PID control based on nonlinear extended observer 2 12
System description 2 12
6.3.2 nonlinear extended observer 2 12
6.3.3 Simulation Example 2 13
6.4 nonlinear PID control 225
6.4. 1 nonlinear PID control algorithm 225
6.4.2 Simulation Example 225
6.5 Active Disturbance Rejection Control 228
ADRC structure 228
6.5.2 Simulation Example 228
Chapter VII PD Robust Adaptive Control 239
7. 1 PD robust control of flexible spacecraft stability239
7. 1. 1 flexible spacecraft modeling 239
7. the design of1.2pd controller.59100.00000000016
7. 1.3 Simulation Example 240
7.2 PI Robust Control of Manipulator Based on Nominal Model 245
7.2. 1 question 245
7.2.2 Design of Robust Control Law 246
Stability analysis 246
7.2.4 Simulation Example 247
7.3 PID control based on anti-saturation 255
Basic principles of anti-saturation 255
7.3.2 PID control based on anti-saturation 255
Simulation example 256
7.4 Model Reference Adaptive Control Based on PD Gain Adaptive Adjustment 259
Problem description 259
7.4.2 Design and analysis of control law 260
7.4.3 Simulation Example 26 1
Chapter 8 Fuzzy PD Control and Expert PID Control 270
8. PD control of stability of1inverted pendulum
8. 1. 1 system description 270
8. 1.2 control law design 270
8. 1.3 Simulation Example 27 1
8.2 PD control of inverted pendulum based on adaptive fuzzy compensation 274
Problem description 274
Design and Analysis of Adaptive Fuzzy Controller275
Stability analysis 276
8.2.4 Simulation Example 277
8.3 Fuzzy PD Control Based on Fuzzy Rule Table 284
8.3. 1 Basic principles
8.3.2 Simulation Example 285
8.4 Fuzzy adaptive tuning PID control288
8.4. 1 fuzzy adaptive tuning PID control principle 288
8.4.2 Simulation Example 29 1
8.5 expert PID control 296
8.5. 1 Expert PID control principle 296
8.5.2 Simulation Example 297
Chapter 9 Neural PID Control 30 1
PID Intelligent Control Based on Single Neuron Network
9. 1. 1 Several typical learning rules 30 1
9. 1.2 single neuron adaptive PID control 30 1
9. 1.3 Improved single neuron adaptive PID control302
9. 1.4 Simulation Example 303
9. 1.5 Single neuron adaptive PID control based on quadratic performance index learning algorithm3005.000000000005
9. 1.6 Simulation Example 306
9.2 PID control based on RBF neural network tuning 309
9.2. 1 RBF neural network model 309
9.2.2 RBF network PID tuning principle 3 10
9.2.3 Simulation Example 3 1 1
PD Control of Inverted Pendulum Based on Adaptive Neural Network Compensation 3 16
Problem description 3 16
9.3.2 Design and Analysis of Adaptive Neural Network 3 16
9.3.3 Simulation Example 3 19
10 chapter PID control based on genetic algorithm tuning 325
10. 1 the basic principle of genetic algorith56866.999999999986
Optimal design of 10.2 genetic algorithm50000.00000000005
10.2. 1 part of genetic algorithm 326
10.2.2 genetic algorithm application step 326
10.3 genetic algorithm for finding the maximum value of function 327
10.3. 1 binary coded genetic algorithm to find the maximum function 327
10.3.2 Real coded genetic algorithm to find the maximum function 33 1.
10.4 PID tuning based on genetic algorithm
On the tuning principle of 10.4. 1 PID based on genetic algorithm506661
PID tuning based on real coded genetic algorithm
10.4.3 PID tuning based on binary coding genetic algorithm
Pd control of 10.4.4 PD based on adaptive on-line genetic algorithm50066.00000000666
10.5 PD control based on friction model compensation 352
10.5. 1 friction model identification 352
10.5.2 Simulation Example 353
Chapter 1 1 PID control of servo system 359
1 1. 1 PID control based on LuGre friction model 26637
11.1.1Friction phenomenon in servosystem 56439.000000000005
LuGre friction model of 1 1. 1.2 servo system 359
1 1. 1.3 Simulation Example 360
1 1.2 PID control based on Stribeck friction model 362
1 1.2. 1 Stribeck friction model description 362
Description of typical servo system 363
1 1.2.3 Simulation Example 364
PID control of three circuits of servo system
1 1.3. 1 Three-loop PID control principle of servo system
1 1.3.2 Simulation Example 372
1 1.4 PID control of dual-mass servo system 375
1 1.4. 1 PID control principle of dual-mass servo system. 46638.66666666666
1 1.4.2 Simulation Example 377
Analog PD+ digital feedforward control of 1 1.5 servo system379
1 1.5. 1 analog PD+ digital feedforward control principle of servo system 379
1 1.5.2 Simulation Example 380
Chapter 12 Iterative learning PID control382
12. 1 Introduction to Iterative Learning Control Method 382
12.2 Basic principles of iterative learning control 382
12.3 basic iterative learning control algorithm 383
12.4 PID-based iterative learning control
1 system description 383
Controller design 384
12.4.3 Simulation Example 384
Chapter 13 Design and Simulation of Other Control Methods 390
13. 1 390 modeling of single inverted pendulum
13.2 PD control of inverted pendulum 39 1
System description 39 1
13.2.2 Simulation Example 39 1
13.3 full-state feedback control of single inverted pendulum18636/66617
1 system description 394
Full state feedback control 395
13.3.3 Simulation Example 395
13.4 input/output feedback linearization 403
System description 403
13.4.2 control law design 404
13.4.3 Simulation Example 404
13.5 inverted pendulum inversion control 408
System description 408
13.5.2 control law design 408
13.5.3 Simulation Example 409
Sliding mode control of 13.6 inverted pendulum
13. 6. 1 problem description 13
13.6.2 control law design
13.6.3 Simulation Example 4 14
13.7 adaptive robust control
Put forward the question of 13. 7+09538. 36438
Design of adaptive control law
13.7.3 Simulation Example 420
H∞ control of 13.8 single inverted pendulum
1 system description 427
H∞ controller requirements 428
On the 13.8.3 H∞ control based on Riccati equation50666.00000668686
13.8.4 H∞ control based on LMI 429
13.8.5 Simulation Example 43 1
13.9 animation demonstration of inverted pendulum control based on graphical user interface. 46636.6866868666 1
13.9. 1 GUI profile 438
The composition of demonstration program 439
Execution of main program 439
GUI design of presentation interface 439
Demonstration step 440
Chapter 14 C++ language design and application of PID real-time control 442
14. 1 C++ realization of control system emulation50000.00000000085
14.2 real-time PID control of the servo system of three-axis flight simulator based on C++ 50666.00000000666
1 control system composition 445
14.2.2 real-time control program analysis 445
14.2.3 Simulation Example 449
Appendix A Description of Common Symbols 459
Reference document 460