Application of Adaptive Fuzzy Wavelet Neural Network in AC Servo Control System

doi:10.3969/j.issn.1000-1093.2015.05.003

Abstract

Abstract: A novel indirect stable adaptive fuzzy wavelet neural（FWNN）controller is proposed to control the nonlinearity, wide variation in loads, time-variation and uncertain disturbance of the high power AC servo system in a certain weapon. In the proposed approach, the self-recurrent wavelet neural network (SRWNN) is employed to construct an adaptive self-recurrent consequent part for each fuzzy rule of Takagi-Sugeno-Kang (TSK) fuzzy model. A back-propagation (BP) algorithm offers the real-time gradient information to the adaptive FWNN controller with the aid of an adaptive SRWNN identifier, which overcomes the effects of parameter variations，load disturbances and other uncertainties effectively. It has a good dynamic performance. The stability of the closed loop system is guaranteed by using the Lyapunov method. The simulation result and the prototype test prove that the proposed method is effective and suitable.

Key words: ordnance science and technology, high power AC servo system, self-recurrent wavelet neural network, indirect stable adaptive fuzzy wavelet neural controller, fuzzy wavelet neural network

CLC Number:

TP273

HOU Run-min， LIU Rong-zhong， GAO Qiang， WANG Li， DENG Tong-bin. Application of Adaptive Fuzzy Wavelet Neural Network in AC Servo Control System[J]. Acta Armamentarii, 2015, 36(5): 781-788.

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