基于实数编码免疫思维进化算法的PID参数整定

PID Parameters Tuning Based on Real-coded Immune Mind Evolutionary Algorithm

在思维进化算法与人工免疫系统的克隆选择算法基础上提出了一种基于实数编码的免疫思维进化算法(IMEA),并将其应用于PID参数的整定。阐述了免疫思维进化算法的基本原理,对免疫思维进化算法PID参数整定进行了仿真研究,并与遗传算法和思维进化算法进行了比较。仿真结果表明所提算法具有快速收敛性,能够很快找到PID参数的最优组合,具有很高的应用价值。

Based on mind evolutionary algorithm and clonal selection principle of artificial im mune systems, a kind of real-coded immune mind evolutionary algorithm （IMEA） is proposed, which is applied to the parameters tuning of PID parameters. The basic theory of immune mind evolutionary algorithm is introduced and the simulation for PID parameters tuning used by IMEA is completed, which is compared with mind evolutionary algorithm （MEA） and genetic algorithm （GA）. The simulation results demonstrate that the algorithm have excellent convergent and can find best PID parameters more quickly. So it has high applicable value.