遗传算法整定PID参数的超磁致伸缩作动器控制策略研究
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摘要
为提高超磁致伸缩作动器的控制精度和效率,在分析超磁致伸缩作动器基本原理的基础上,首先建立了作动器的控制系统数学模型;然后,利用遗传算法整定PID参数的方式对作动器进行了控制,并利用Simulink搭建作动器控制框图进行了仿真分析;最后,与传统PID控制效果进行的对比分析。结果表明:所提出的基于遗传算法整定PID参数的方法可以有效提高系统控制效果。
In order to improve the control precision and efficiency of giant magnetostrictive actuator,based on the analysis of the basic principle of giant magnetostrictive actuator,a mathematical model for the actuator control system is established.Then,the genetic algorithm tuning PID parameters are used to control actuator,and then simulation analysis is carried out based on Simulink,by which the actuator control block is established.The result shows that the control effect of genetic algorithm tuningPID parameters is better while it is compared with that of traditional PID.
In order to improve the control precision and efficiency of giant magnetostrictive actuator,based on the analysis of the basic principle of giant magnetostrictive actuator,a mathematical model for the actuator control system is established.Then,the genetic algorithm tuning PID parameters are used to control actuator,and then simulation analysis is carried out based on Simulink,by which the actuator control block is established.The result shows that the control effect of genetic algorithm tuningPID parameters is better while it is compared with that of traditional PID.
引文
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[2]JALIL M H A,MARZAKI M H,KASUAN N,et al.Implementation of anti windup scheme on PID controller for regulating temperature of glycerin bleaching process[C]//International Conference on System Engineering and Technology.Los Angeles:IEEE,2013.
[3]CORCOLLE R,DANIIEL L,BOUILLAULT F.Optimal design of magnetostrictive composites:An analytical approach[J].IEEE Transactions on Magnetics,2008,44(1):17-23.
[4]ZHU Z,LIU K,HE Y,et al.Model free analysis and tuning of PID controller[C]//Asian Control Conference.Istanbul:ASCC,2013.
[5]ZHANG J,LIU L,LI H,et al.PID tuning based on improved quantum genetic algorithm[C]//International Symposium on Computational Intelligence&Design.Hangzhou:ISCID,2013.
[6]SHAO X G,XIAO L Q,HAN C C.Optimization of PID parameters based on genetic algorithm and interval algorithm[C]//中国控制与决策会议论文集(1).桂林:东北大学出版社,2009.