NDLI: Tuning PID control parameters on hydraulic servo control system based on chaos quantum-behaved particle swarm optimization algorithm

Content Provider	IEEE Xplore Digital Library
Author	Youxin Luo Lingfang Li
Copyright Year	2010
Description	Author affiliation: College of Mechanical Engineering, Hunan University of Arts and Science, Changde, 415000, China (Youxin Luo; Lingfang Li)
Abstract	The PID control parameters are very important to performance of hydraulic servo control system and how to find rapidly the optimum values of PID control parameters is very difficult problem. To overcome the problem of low convergence speed and sensitivity to local convergence with the traditional quantum-behaved particle swarm optimization (QPSO) to handle optimum problem, a novel method of judging the local convergence by the variance of the population's fitness was proposed, and the chaos quantum-behaved particle swarm optimization algorithm (CQPSO) was proposed. The program CQPSO1.0 was developed. Based on Matlab/simulink software and taking the IATE standards of optimization design as objective function, the proposed method was applied for the optimization of the three parameters of PID controller of electric-hydraulic servo system of 6-DOF parallel platform. Simulation results show that the proposed parameter optimum method is an effective tuning strategy and has good performance.
Starting Page	1861
Ending Page	1864
File Size	305358
Page Count	4
File Format	PDF
ISBN	9781424473311
e-ISBN	9781424473304
DOI	10.1109/ICLSIM.2010.5461316
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-01-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chaos Chaos searching Electric-hydraulic servo system Three-term control Control systems Educational institutions PID parameters tuning Servosystems Particle swarm optimization Mechanical engineering Convergence Design optimization Matlab/Simulink Servomechanisms QPSO
Content Type	Text
Resource Type	Article

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