신경망 보상기를 이용한 PMSM의 간단한 지능형 강인 위치 제어

A very simple control approach using neural network for the robust position control of a Permanent Magnet Synchronous Motor(PMSM) is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust PMSM system approximately liearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network IS composed by a feedforward recall and error back-propagation training Since the total number of nodes are only eight, this system can be easily realized by the general microprocessor. During the nonnal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque And the state space analysis is performed to obtain the state feedback gains systematically In addition, the robustness IS also obtained without affecting overall system response This method IS realized by a floating-point Digital Signal Processor DS1102 Board (TMS320C31J. The basic DSP software is used to write C program, which is compiled by using ANSI -C style function prototypes