摘要
本文依据H∞控制理论,结合H∞混合灵敏度加权函数的选择,提出了一种
SISO系统基于多目标遗传算法(MOGAS)的H∞混合灵敏度加权函数优化控制设计方法。针对H∞控制方法存在的保守性和加权函数选取无明确方法的问题,做了算法的改进。给出了一种新的加权函数选取型式,在此基础上根据多目标遗传算法进行了加权函数的优化选取,并确立了控制器。
仿真结果表明,本文方法对外部扰动、对象模型的结构和非结构不确定性摄动具有灵敏度低、跟踪速度快、稳定裕度好等优点,使系统动态性能比常规H∞、PID和Smith预估控制方法有了明显改善
In this thesis, an H∞controller parameters optimizing method of mixed weighted sensitivity function of SISO system based on the Genetic Algorithms is discussed. Aiming at the delay and no specific selection of weighting functions, a new algorithm is brought forward. A new selection of weighting functions is given and a controller is obtained using the weighting functions that are selected on the basis of MOGAS.
Experiment study results show that systems using controllers designed by this method have low sensitivity, good stability and strong robustness for uncertainty and have better closed-loop dynamic performance when comparing with the normal H∞, PID and Smith controller.
Zhang Xue Gang(control theory and control engineering)
Directed by prof. Li Da Zhong
引文
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