期刊名称：International Journal on Smart Sensing and Intelligent Systems
印刷版ISSN：1178-5608
出版年度：2015
卷号：8
期号：2
页码：1406-1423
出版社：Massey University
摘要：A novel intelligent neural network control scheme which integrates the merits of fuzzyinference, neural network adaptivity and simple PID method is presented in this paper. This controlmethod overcomes the defects existed in the traditional variable frequency induction motor drivenhydraulic source, such as slow response, poor control precision, easy to overshoot. Permanentmagnet synchronous motor driven constant pump hydraulic system is designed instead of commonmotor, energy saving, fast response and easy to realize closed loop control. System uses thestructure of the combination of neural network control and RBF network online identification. Theparameters of the controller are optimized by PSO algorithm offline and error back propagation(BP) algorithm offline, and a RBF network is built to identify the system online. The hydraulicpower system’s control simulation experiments are conducted, and the experimental results at thetypical working conditions of the hydraulic source show that the controller and its optimizationalgorithm can effectively improve the system performance, and the system has no steady-state error,good dynamic performance and good robustness, superior to conventional fuzzy controller and PIDcontroller.
