Application of Particle Swarm Optimization Algorithm on Robust PID Controller Tuning

The performance of the PID controller may deteriorate when the operating condition of a process fluctuates. A robust parameter tuning method to improve the PID controller performance under bounded model uncertainty is presented. First an enhanced performance criterion is proposed to reduce the overs...

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Bibliographic Details
Published inAdvances in Natural Computation pp. 948 - 957
Main Authors Zhao, Jun, Li, Tianpeng, Qian, Jixin
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2005
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Exact sciences and technology
Integral Squared Error
Optimal Power Flow
Particle Swarm Optimization
Particle Swarm Optimization Algorithm
Tuning Method
Robust control
Uncertainty
Evolutionary algorithm
Minimax method
Swarm intelligence
Nonlinear problems
Neural network
Modeling
Differential integral proportional control
Operating conditions
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Summary:The performance of the PID controller may deteriorate when the operating condition of a process fluctuates. A robust parameter tuning method to improve the PID controller performance under bounded model uncertainty is presented. First an enhanced performance criterion is proposed to reduce the overshoot and large control move. Then the robust tuning problem is formulated as a Min-Max optimization. Particle Swarm Optimization (PSO) is applied to solve the nonlinear, non-differentiable problem. Examples are given to demonstrate the effectiveness of the proposed method. Compared with other PID tuning methods, the result shows that better performance can be achieved with the model parameter fluctuation.
ISBN:9783540283201
354028320X
3540283234
9783540283232
ISSN:0302-9743
1611-3349
DOI:10.1007/11539902_118