摘要
针对传统的PID控制中参数整定的难题,采用智能控制技术优化PID参数,利用神经网络进行系统辨识,建立对象模型;在此模型基础上,运用遗传算法寻优PID控制参数,采用变交叉概率和变异概率自适应遗传算法寻优得到PID控制参数,与传统的整定结果相比较,遗传算法优化效果更好,最终达到最优的控制效果.
The choice and definition of the parameters of PID are very difficult for a long time. In this paper we optimize PID parameters with intelligent control technologies and distinguish system with nerve network and set up target model; On the basis of this model , the genetic algorithm（ GA） is used to seek excellent PID control parameters. The effect of GA optimizing, which adapts the self - adaptive GA of variation crossing probability and variation probability to get the parameters of PID controller, is prior to traditional definition, and gets the optimum result of control finally.
出处
《邵阳学院学报（自然科学版）》
2006年第1期35-37,78,共4页
Journal of Shaoyang University：Natural Science Edition
关键词
PID控制
参数优化
遗传算法
神经网络
PID control
optimizing parameter
genetic algorithm（GA）
nerve network
