摘要
提出了一种基于模糊推理与遗传算法的最优PID控制器的设计方法 .该控制器由离线和在线 2部分组成 .在离线部分 ,以系统响应的超调量、上升时间及调整时间为性能指标 ,利用遗传算法搜索出一组最优的PID参数K p ,T i 及T d ,作为在线部分调节的初始值 ;在在线部分 ,采用一个专用的PID参数优化程序 ,以离线部分获得的K p ,T i 及T d 为基础 ,根据系统当前的误差e和误差变化率 e ,通过模糊推理在线调整系统瞬态响应的PID参数 ,以确保系统的响应具有最优的动态和稳态性能 .计算机仿真结果表明 ,与传统的PID控制器相比 ,这种最优PID控制器具有良好的控制性能和鲁棒性能 。
An optimal PID controller is proposed based on fuzzy inference and genetic algorithms, which is called the optimal fuzzy GA PID controller. It consists of the off line part and the on line part. In the off line part, by taking the overshoot, rise time, and setting time of system response as the performance indexes and by means of the genetic algorithm, a group of optimal PID parameters K p *, T i * and T d * are obtained, which are used as the initial values for the on line tuning of PID parameters. In the on line part, based on K p *, T i *, and T d * and according to the system's current error e and its time derivative , a dedicated program is written, which is used to optimize and adjust the PID parameters on line through a fuzzy inference system to ensure that the system response has optimal dynamic and steady state performances. The results of computer simulation show that it is more excellent than the conventional PID controllers in the dynamic behavior of system response. This kind of controller possesses good control performance and robust performance and can be used to control different kinds of objects and processes.
出处
《中南工业大学学报》
CSCD
北大核心
2002年第4期419-423,共5页
Journal of Central South University of Technology(Natural Science)
基金
中国科学院机器人学开放研究实验室基金资助项目(RL2 0 0 0 0 2 )