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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

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Related citation:WANG Guo-liang,Yan Wei Wu,Shao Hui He.Multi-objective optimization based on Genetic Algorithm for PID controller tuning[J].Journal of Harbin Institute Of Technology(New Series),2009,16(1):71-74.DOI:10.11916/j.issn.1005-9113.2009.01.015.
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Multi-objective optimization based on Genetic Algorithm for PID controller tuning
Author NameAffiliation
WANG Guo-liang Institute of Automation, Shanghai Jiaotong University, Shanghai 200240, China 
Yan Wei Wu Institute of Automation, Shanghai Jiaotong University, Shanghai 200240, China 
Shao Hui He Institute of Automation, Shanghai Jiaotong University, Shanghai 200240, China 
Abstract:
To get the satisfying performance of a PID controller, this paper presents a novel Pareto-based multi-objective genetic algorithm (MOGA), which can be used to find the appropriate setting of the PID controller by analyzing the pareto optimal surfaces. Rated settings of the controller by two criteria, the error between output and reference signals and control moves, are listed on the pareto surface. Appropriate setting can be chosen under a balance between two criteria for different control purposes. A controller tuning problem for a plant with high order and time delay is chosen as an example. Simulation results show that the method of MOGA is more efficient compared with traditional tuning methods.
Key words:  multi-objective optimization  genetic algorithms  PID controller
DOI：10.11916/j.issn.1005-9113.2009.01.015
Clc Number:TP18;TP273
Fund:

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