基于混沌搜索的模糊控制器参数最优设计

基于混沌变量，本文提出一种模糊控制器最优设计方案．离线优化采用混沌算法，将混沌因子引入到模糊控制器参数域的优化搜索中，用载波方式将优化变量转变成混沌变量，再利用混沌运动的遍历性和随机性直接寻优，得到模糊控制器参数的全局次优解．在线优化采用共轭梯度下降法，把混沌搜索后得到的全局次优值作为梯度下降搜索的初始值，实现混沌全局粗搜索和梯度下降局部细搜索相结合的优化目的，能很快找到模糊控制器参数的全局最优解．最后对算法的收敛性进行了证明．

OPTIMAL DESIGN OF FUZZY CONTROLLER PARAMETERS BASED ON CHAOS SEARCH

Based on chaos variables, an optimal design scheme for of fuzzy controller is proposed in the paper. A chaos algorithm is used in off line optimization, and chaos factors are incorporated into optimized searching of fuzzy controller parameters. The optimal variables are transformed into chaotic variables by carrier wave. Then, we take advantage of ergodicity and randomness of chaos dynamics in the searching process, and get the approximate global optimal values of the parameters. A conjugate gradient descent algorithm is used in on line optimization, and the initial values of gradient descent searching are used as approximate global optimal values of chaos searching, and controller parameters are quickly optimized by means of combination of chaos global searching and gradient descent local searching. Finally, convergency of the algorithm is proved.