Practical PID Control

Front Cover
Springer Science & Business Media, Nov 3, 2006 - Technology & Engineering - 314 pages

Proportional–integral–derivative (PID) controllers are the most adopted controllers in industrial settings because of the advantageous cost/benefit ratio they are able to provide. Despite their long history and the know-how gained from years of experience, the availability of microprocessors and software tools and the increasing demand for higher product quality at reduced cost have stimulated researchers to devise new methodologies to improve their performance and make them easier to use.

Practical PID Control covers important issues that arise when a PID controller is to be applied in practical cases. Its focus is on those functionalities that can provide significant improvements in performance in combination with a sound tuning of parameters. In particular, the choice of filter to make the controller proper, the use of a feedforward action and the selection of an anti-windup strategy are addressed. Further, the choice of the identification algorithm and of the model reduction technique are analysed in the context of model-based PID control. Widely adopted PID-based control architectures (ratio and cascade control) and performance assessment are also covered. For these topics, recent contributions are explained and compared with more standard approaches. A large number of simulation and experimental results are provided in order better to illustrate the different methodologies and to discuss their pros and cons. Practical PID Control is a helpful and instructive reference for researchers, graduate students and practitioners in process control.

 

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Contents

Basics of PID Control
1
12 Feedback Control
2
13 OnOff Control
3
142 Integral Action
5
143 Derivative Action
6
15 Structures of PID Controllers
7
16 Modifications of the Basic PID Control Law
8
162 Setpoint Weighting
11
56 Feedforward Action for Disturbance Rejection
140
57 Conclusions
143
PlugControl
145
63 Timeoptimal PlugControl
149
633 Practical Considerations
152
634 Simulation Results
153
635 Experimental Results
157
636 Discussion
163

163 General ISAPID Control Law
13
18 Choice of the Controller Type
15
19 The Tuning Issue
16
110 Automatic Tuning
18
Derivative Filter Design
19
23 Ideal vs Series Form
22
24 Simulation Results
27
25 Fourparameters Tuning
33
Antiwindup Strategies
35
33 Antiwindup Techniques
37
332 Conditional Integration
38
334 Combined Approaches
41
335 Automatic Reset Implementation
42
34 Simulation Results
44
35 Experimental Results
50
352 Temperature Control
55
36 Conclusions
60
Setpoint Weighting
61
43 Variable Setpoint Weighting
63
432 Simulation Results
67
44 Fuzzy Setpoint Weighting
72
442 Tuning Procedure
73
443 Simulation Results
75
444 Experimental Results
82
45 Discussion
87
46 Conclusions
91
Use of a Feedforward Action
93
53 Nonlinear Causal Feedforward Action
96
531 Simulation Results
98
532 Experimental Results
103
Continuoustime Case
109
542 Methodology
110
543 Simulation Results
116
544 Experimental Results
126
Discretetime Case
130
552 Simulation Results
133
553 Experimental Results
136
Identification and Model Reduction Techniques
164
721 Openloop Identification Techniques
166
722 Closedloop Identification Techniques
173
73 SOPDT Systems
180
732 Closedloop Identification Techniques
191
74 Discussion
192
75 PID Control of Highorder Systems
193
751 Internal Model Control Design
194
752 Process Model Reduction
195
753 Controller Reduction
198
754 Simulation Results
199
755 Discussion
205
76 Conclusions and References
207
Performance Assessment
209
82 Generalities
210
832 Assessment of Performance
212
833 Assessment of PID Control Performance
216
84 Deterministic Performance Assessment
222
841 Useful Functionalities
223
842 Optimal Performance for Singleloop Systems
232
843 PID Tuning Assessment
234
85 Conclusions and References
250
Control Structures
251
922 Relay Feedback Sequential Autotuning
253
924 Simultaneous Identification Based on Step Response
257
926 Tuning of the General Cascade Control Structure
260
927 Use of a Smith Predictor in the Outer Loop
263
928 Two Degreeoffreedom Control Structure
265
93 Ratio Control
267
932 The Blend Station
268
933 Dynamic Blend Station
280
94 Conclusions
291
Experimental Setups
295
A2 Temperature Control Apparatus
296
References
298
Index
309
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About the author (2006)

Antonio Visioli’ research interests include industrial robot control and trajectory planning, dynamic inversion-based control and process control. He is a reviewer for several control-related journals and collaborates wit hthe industrial concerns:Yokogawa Italia srl (www.yokogawa.it) and with Paneutec srl (www.paneutec.com) doing research ob performance assessment and conducting seminars for them.

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