摘要
首次采用遗传算法实现小脑模型控制固定增益的最优设计，并采用超调受限最优化方法进行优化，而且结合线材缠绕液压系统张力控制进行了控制仿真试验．同时采用遗传算法对同一被控对象进行了ＰＩＤ最优控制设计．试验结果表明本文方法是有效的．它克服了以往小脑模型控制设计的反复试错的缺点，进而使控制系统设计工作量大大减少．试验还表明，采用遗传算法对小脑模型控制的固定增益进行最优设计，比对ＰＩＤ最优控制设计容易。
Using genetic algorithm(GA),the optimal design for cerebellar model articulation controller(CMAC) is first carried out with the limited overshoot. In addition,the proposed method is proved to be effective by the simulation of the wire tension CMAC controller optimal design.The simulation is also compared to the wire optimal PID controller in this paper.This method not only can overcome the too much times by traditional trialanderror design method, but also is able to obtain optimal control system design.The simulation results show that the proposed design method is more stable and easier than optimal PID.
出处
《信息与控制》
CSCD
北大核心
1997年第6期455-458,共4页
Information and Control
基金
中国博士后科学基金
关键词
小脑模型
遗传算法
控制系统
最优设计
cerebellar model articulation controller (CMAC),genetic algorithm(GA),optimization
