基于人工免疫多模态函数优化的PID整定

PID Tuning with Immune-based Multimodal Function Optimization

提出一种基于人工免疫多模态函数优化的PID(Proportional Integral Derivative)参数离线整定控制器的算法.该算法通过设计多模态函数,搜索出多模态函数的所有峰值点,这些峰值点即是极优的Kp,Ki,Kd参数组合集.同时,该算法将无限个数据聚类成有限个数据,决策者可以根据实际应用要求,在有限个数据内选择最合适的最优决策.Matlab仿真结果证明了该算法的优越性和有效性.

In this paper,a novel artificial immune network for multimodal function optimization（Opt-aiNet） algorithm is proposed,which is applied to the controller for the out-line tuning of PID（Proportional Integral Derivative） parameters.The Opt-aiNet algorithm locates all peaks of multimodal function by designing multimodal function,and all the peaks are just the optimal combined parameters set of Kp、Ki and Kd.This algorithm clusters the infinity data to the finitude data.The decision maker can select the optimum decision within finitude data according to the requirements of application.The results of Matlab simulation show that the proposed algorithm is valid and superior.