摘要
提出一种基于改进遗传算法的自适应模糊控制策略 ,通过优化控制器中非线性量化函数及自适应控制表达式等中的关键参数 ,得到基于加权 ITAE指标的满意控制 .经过大量仿真研究 ,证明其对多输入多输出系统、混沌系统、滞后系统等复杂系统的控制有良好效果 .
An improved genetic algorithm based self adaptive controlling strategy is presented. Satisfactory control based on the index of weighted ITAE is achieved by optimizing the key parameters in nonlinear quantization function and self adaptive formula of controller. With many simulations, the new approach has be proved to have excellent performance to complex systems such as MIMO systems, chaotic systems, systems with delay.
出处
《信息与控制》
CSCD
北大核心
2001年第3期244-248,共5页
Information and Control
基金
国家自然科学基金重大项目!( 79990 85 0 )
国家自然科学基金!( 696740 41)
关键词
复杂系统
智能控制
新算法
仿真
遗传算法
improved genetic algorithm, adaptive genetic arithmetic operators, nonlinear quantization factor, self adaptive fuzzy controller, ITAE index
