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E-book: PID Controller Tuning Using the Magnitude Optimum Criterion

  • Format: PDF+DRM
  • Pub. Date: 01-Nov-2014
  • Publisher: Springer International Publishing AG
  • Language: eng
  • ISBN-13: 9783319072630
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  • Format: PDF+DRM
  • Pub. Date: 01-Nov-2014
  • Publisher: Springer International Publishing AG
  • Language: eng
  • ISBN-13: 9783319072630
Other books in subject:

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An instructive reference that will help control researchers and engineers, interested in a variety of industrial processes, to take advantage of a powerful tuning method for the ever-popular PID control paradigm.

This monograph presents explicit PID tuning rules for linear control loops regardless of process complexity. It shows the reader how such loops achieve zero steady-position, velocity, and acceleration errors and are thus able to track fast reference signals. The theoretical development takes place in the frequency domain by introducing a general-transfer-function-known process model and by exploiting the principle of the magnitude optimum criterion. It is paralleled by the presentation of real industrial control loops used in electric motor drives. The application of the proposed tuning rules to a large class of processes shows that irrespective of the complexity of the controlled process the shape of the step and frequency response of the control loop exhibits a specific performance. This specific performance, along with the PID explicit solution, formulates the basis for developing an automatic tuning method for the PID controller parameters which is a problem often met in many industry applications—temperature, pH, and humidity control, ratio control in product blending, and boiler-drum level control, for example. The process of the model is considered unknown and controller parameters are tuned automatically such that the aforementioned performance is achieved. The potential both for the explicit tuning rules and the automatic tuning method is demonstrated using several examples for benchmark process models recurring frequently in many industry applications.

Part I Introduction and Preliminaries
1 Overview
3(8)
1.1 Introduction
3(2)
1.2 Target of the Proposed Theory
5(1)
1.3 State of the Art---The Magnitude Optimum Criterion
6(2)
1.3.1 Type-I Control Loops
6(1)
1.3.2 Type-II Control Loops
7(1)
1.3.3 Type-III Control Loops
8(1)
1.4 Automatic Tuning of PID Controllers
8(3)
References
9(2)
2 Background and Preliminaries
11(20)
2.1 Definitions and Preliminaries
11(3)
2.2 Frequency Domain Modeling
14(1)
2.3 Internal Stability
15(3)
2.4 Robustness
18(1)
2.5 Type of Control Loop
19(2)
2.6 Sensitivity and Complementary Sensitivity Function
21(2)
2.7 The Magnitude Optimum Design Criterion
23(3)
2.8 Summary
26(5)
References
27(4)
Part II Explicit Tuning of the PID Controller
3 Type-I Control Loops
31(54)
3.1 Introduction
32(1)
3.2 Conventional PID Tuning Via the Magnitude Optimum Criterion
33(9)
3.2.1 I Control
34(1)
3.2.2 Preservation of the Shape of the Step and Frequency Response
35(2)
3.2.3 PI Control
37(1)
3.2.4 PID Control
38(3)
3.2.5 Drawbacks of the Conventional Tuning Method
41(1)
3.2.6 Why PID Control?
41(1)
3.3 Revised PID Tuning Via the Magnitude Optimum Criterion
42(4)
3.4 Performance Comparison Between Conventional and Revised PID Tuning
46(20)
3.4.1 Plant with One and Two Dominant Time Constants
46(1)
3.4.2 Plant with Five Dominant Time Constants
47(2)
3.4.3 A Pure Time Delay Process
49(2)
3.4.4 A Nonminimum Phase Process
51(1)
3.4.5 A Process with Large Zeros
51(2)
3.4.6 Comments on Pole-Zero Cancellation
53(2)
3.4.7 Comments on Disturbances Rejection
55(2)
3.4.8 Rejection of Output Disturbances
57(3)
3.4.9 Rejection of Input Disturbances
60(2)
3.4.10 Robustness to Model Uncertainties
62(4)
3.5 Performance Comparison Between Revised PID Tuning and Other Methods
66(10)
3.5.1 Internal Model Control
67(3)
3.5.2 Ziegler-Nichols Step Response Method
70(1)
3.5.3 Simulation Results
71(5)
3.6 Explicit Tuning of PID Controllers Applied to Grid Converters
76(6)
3.6.1 Simplified Control Model and Parameters
77(5)
3.7 Summary
82(3)
References
83(2)
4 Type-II Control Loops
85(32)
4.1 Introduction
85(3)
4.2 Conventional PID Tuning Via the Symmetrical Optimum Criterion
88(6)
4.2.1 I Control
88(2)
4.2.2 PI Control
90(1)
4.2.3 PID Control
90(4)
4.2.4 Drawbacks of the Conventional Tuning
94(1)
4.3 Revised PID Tuning Via the Symmetrical Optimum Criterion
94(4)
4.4 Performance Comparison Between Conventional and Revised PID Tuning
98(12)
4.4.1 Plant with One Dominant Time Constant
98(3)
4.4.2 Plant with Two Dominant Time Constants
101(2)
4.4.3 A Non-minimum Phase Process
103(3)
4.4.4 Plant with Long Time Delay
106(1)
4.4.5 Plant with Large Zeros
106(4)
4.5 DC Link Voltage Control on an AC/DC Converter-Type-II Control Loop
110(4)
4.5.1 Simplified Control Model and Parameters
111(1)
4.5.2 Modeling of the Control Loop in the Frequency Domain
111(3)
4.6 Summary
114(3)
References
114(3)
5 Type-III Control Loops
117(44)
5.1 Introduction
117(2)
5.2 PID Tuning Rules for Type-III Control Loops
119(14)
5.2.1 Pole-Zero Cancellation Design
119(4)
5.2.2 Revised PID Tuning Rules
123(4)
5.2.3 Simulation Results
127(6)
5.3 Explicit PID Tuning Rules for Type-p Control Loops
133(25)
5.3.1 Extending the Design to Type-p Control Loops
135(11)
5.3.2 Simulation Results
146(8)
5.3.3 Robustness Performance
154(4)
5.4 Summary
158(3)
References
159(2)
6 Sampled Data Systems
161(38)
6.1 Type-I Control Loops
161(10)
6.1.1 Performance Comparison Between Analog and Digital Design in Type-I Control Loops
165(6)
6.2 Type-II Control Loops
171(8)
6.2.1 Performance Comparison Between Analog and Digital Design in Type-II Control Loops
174(5)
6.3 Type-III Control Loops
179(17)
6.3.1 Performance Comparison Between Analog and Digital Design in Type-III Control Loops
181(7)
6.3.2 Sampling Time Effect Investigation in Type-III Control Loops
188(8)
6.4 Summary
196(3)
References
196(3)
Part III Automatic Tuning of the PID Controller
7 Automatic Tuning of PID Regulators for Type-I Control Loops
199(44)
7.1 Why Automatic Tuning?
199(3)
7.2 The Algorithm of Automatic Tuning of PID Regulators
202(10)
7.2.1 Integral Control of the Approximate Plant
203(1)
7.2.2 Integral Control of the Real Plant
204(1)
7.2.3 Proportional-Integral Control
204(1)
7.2.4 Proportional-Integral-Derivative Control
205(1)
7.2.5 The Tuning Process
206(4)
7.2.6 Starting up the Procedure
210(2)
7.3 Simulation Examples
212(12)
7.3.1 Plant with One Dominant Time Constant
212(3)
7.3.2 Plant with Two Dominant Time Constants
215(1)
7.3.3 Plant with Dominant Time Constants and Time Delay
216(2)
7.3.4 Plant with Dominant Time Constants, Zeros, and Time Delay
218(3)
7.3.5 A Nonminimum Phase Plant with Time Delay
221(3)
7.4 Automatic Tuning for Processes with Conjugate Complex Poles
224(12)
7.4.1 Direct Tuning of the PID Controller for Processes with Conjugate Complex Poles
225(3)
7.4.2 Automatic Tuning of the PID Controller for Processes with Conjugate Complex Poles
228(6)
7.4.3 Simulation Examples
234(2)
7.5 Summary
236(7)
References
240(3)
8 Changes on the Current State of the Art
243(6)
8.1 The Magnitude Optimum Criterion---Present and Future of PID Control
243(4)
8.2 Open Issues and Future Work
247(2)
References
247(2)
Appendix A The Magnitude Optimum Criterion 249(4)
Appendix B Analog Design-Proof of the Optimal Control Law 253(16)
Appendix C Digital Design-Proof of the Optimal Control Law 269(24)
Index 293
Dr. Eng. Konstantinos G. Papadopoulos is with ABB Switzerland (Department of Medium Voltage Drives) working as a control software development engineer for the ABB's ACS MV Drives family products. Specifically, control software development is associated with modelling of both induction and synchronous motor drives on a simulation basis, design of the control loops involved within the control principle of the motor, tuning of the involved PI/PID controllers and finally software development/integration of the simulation model onto the ABB's real time platform used in medium voltage drives.