Research On The Method Of H_∞ Weighting Functions Optimizing Control Based On The Multi-Objective Genetic Algorithms

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...