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  • 标题:Optimization Design Based On Self-Adapted Ant Colony and Genetic Mix Algorithm for Parameters of PID Controller
  • 本地全文:下载
  • 作者:Wang Xiao-Yu
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2015
  • 卷号:8
  • 期号:7
  • 页码:411-422
  • DOI:10.14257/ijhit.2015.8.7.37
  • 出版社:SERSC
  • 摘要:This paper presents a method of optimized PID parameter self-adapted ant colony algorithm with aberrance gene, based on ant colony algorithm. This method overcomes genetic algorithm's defects of repeated iteration, slower solving efficiency, ordinary ant colony algorithm's defects of slow convergence speed, easy to get stagnate, and low ability of full search. For a given system, the results of simulation experiments which compare to the result of Z-N optimization and evolution of genetic algorithm optimization and evolution of ant colony system optimization, it has more excellent performance in finding best solution and convergence, the PID parameters also have optimality, system possesses dynamic controlling and performance. The experiments show that this method has its practical value on controlling other objection and process.
  • 关键词:PID controller; ant colony algorithm; genetic algorithm; fitness function; ; ACS-GA algorithm
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