Research of process controls parameter optimal selection based on improved genetic algorithm

摘要：

PID control algorithm has been extensively used in process controls.But it is difficult to tune the PID parameters in the controllers.This paper proposes a solution to do optimal selection of process control parameters by simulated annealing and genetic algorithm.Furthermore,fuzzy reasoning is adopted to modify crossover probability and mutation probability according to the characteristics of the population in genetic algorithms,rather than using fixed parameters.And so,the global optimum can be converged at quickly.The verified algorithm can be applied to obtain the best control parameters of the fitness function with least-error and least-overshoot optimization criterion.A better control effect is achieved in the process simulation of the second order system’s response using these control parameters,which indicates that this improved algorithm for process control parameters’ optimal selection has a high value in practice.

关键词： simulated annealing genetic algorithms fuzzy reasoning fitness function process control

作者: G.F. Yan X.H. Huang F. Tan

作者单位: Institute of Automation Engineering,University of Electronic Science and Technology of China,Cheng Du,Si Chuan,China

会议类型: 国际会议

会议名称: The World Forum on Smart Materials and Smart Structures Technology(SMSST07)(2007年世界智能材料与智能结构技术论坛)

会议地点: 重庆·南京

会议语种:英文

在线出版日期: 2007-05-01（万方平台首次上网日期，不代表论文的发表时间）