Title :
AC servo system based on MEC optimization and fuzzy neural network control
Author :
Liu Qingsong ; Yue Jinping
Author_Institution :
Sch. of Electr. & Mech. Eng., Jiaxing Univ., Jiaxing, China
Abstract :
To satisfy the requirements of higher accuracy and faster response in AC servo system, a system with a fuzzy neural network controller based on mind evolutionary computation (MEC) optimization was designed. The controller combined the advantage of fast searching optimization of MEC and the advantage of not depending on controlled plant of fuzzy neural network controller. This method uses MEC to search the optimal mean, the optimal standard deviation and the optimal weights that connect membership layer and rule layer. Simulation and experimental results verified the effectiveness of the method. The results show that this method has good control effect on both system regulating and set-point following. For AC system in practice, this method has quite good disturbance resistance and strong robustness, and both dynamic and steady performances were improved evidently.
Keywords :
evolutionary computation; fuzzy control; neurocontrollers; search problems; servomechanisms; AC servo system; MEC; fuzzy neural network control; mind evolutionary computation; optimal mean deviation; optimal standard deviation; searching optimization; Electronic mail; Evolutionary computation; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Optimization; Servomotors; AC servo system; Fuzzy neural network controller; Mind evolutionary computation;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768