DocumentCode :
2642042
Title :
Adaptive Genetic Algorithm Based Optimal PID Controller Design of an Active Magnetic Bearing System
Author :
Chen, Hung-Cheng
fYear :
2008
fDate :
18-20 June 2008
Firstpage :
603
Lastpage :
603
Abstract :
This paper proposes a novel adaptive genetic algorithm (AGA) for the multi-objective optimization design of a PID controller and applies it to the control of a real active magnetic bearing (AMB) system. The performances of the AGA are compared with that of the simple genetic algorithm (SGA) in optimizing dynamic responses of the controlled AMB. It shows that because of the proposed AGA can adjust the parameters adaptively according to the value of individual fitness and dispersion degree of population, this algorithm realizes the goals of maintaining diversity in the population and sustaining the convergence capacity of the genetic algorithm. The problems of convergence and prematurity occurred in SGA are then solved. The dynamic model of AMB system for axial motion is also presented, together with experimental and simulation results to verify its availability and good dynamic response.
Keywords :
adaptive control; control system synthesis; convergence; genetic algorithms; magnetic bearings; optimal control; three-term control; active magnetic bearing system; adaptive genetic algorithm; axial motion; convergence capacity; dynamic model; multiobjective optimization design; optimal PID controller design; Adaptive control; Algorithm design and analysis; Control systems; Convergence; Design optimization; Genetic algorithms; Magnetic levitation; Optimal control; Programmable control; Three-term control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
Type :
conf
DOI :
10.1109/ICICIC.2008.116
Filename :
4603792
Link To Document :
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