NDLI: Hybrid genetic algorithm and application to PID controllers

Content Provider	IEEE Xplore Digital Library
Author	Liqing Xiao Chengchun Han Xiaoju Xu Weiyong Huang
Copyright Year	2010
Description	Author affiliation: Xuzhou Institute of Technology, 221008, China (Liqing Xiao; Chengchun Han; Xiaoju Xu; Weiyong Huang)
Abstract	In order to overcome simple genetic algorithm detects of worse local searching ability and premature convergence, a hybrid genetic algorithm was proposed. The novel algorithm was based on particle swarm optimization and interval algorithm, and applied to parameters optimization of PID controllers by applying particle swarm optimization to the mutation operation, and employing interval algorithm in population initialization of genetic algorithm. The simulation and experimental results show that the novel algorithm is superior to simple genetic algorithm, can overcome premature phenomena, improve the convergence precision and speed, reduce the influence of random initial population, and has advantages such as excellent optimization ability, high rate of convergence and good stability.
Starting Page	586
Ending Page	590
File Size	262863
Page Count	5
File Format	PDF
ISBN	9781424451814
DOI	10.1109/CCDC.2010.5498979
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-05-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Stability Three-term control Genetic mutations Premature Convergence Optimization methods Genetic Algorithm Particle swarm optimization Genetic algorithms Convergence Design engineering Interval Algorithm Evolution (biology) Particle Swarm Optimization
Content Type	Text
Resource Type	Article

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