FPGA-based neural fuzzy controller design for PMLSM drive Online publication date: Sat, 31-Jan-2015
by Ying-Shieh Kung, Le Thi Van Anh
International Journal of Power Electronics (IJPELEC), Vol. 3, No. 3, 2011
Abstract: Based on the technology of field programmable gate array (FPGA), a realisation of fuzzy control (FC) system with radial basis function neural network (RBF NN) tuning is presented to a permanent magnet linear synchronous motor (PMLSM) drive in this paper. Firstly, a mathematic model of the PMLSM drive is defined; then to increase the performance of the PMLSM drive system, an FC constructed by a fuzzy basis function and its parameter adjustable mechanism using RBF NN is applied to the position control loop of the PMLSM drive system to cope with the effect of the system dynamic uncertainty and the external load. Secondly, FPGA by using finite state machine (FSM) method is presented to realise the aforementioned controllers, and VHSIC hardware description language (VHDL) is adopted to describe the circuit of the FSM. Finally, an experimental system is established to verify the effectiveness of the proposed FPGA-based neural fuzzy control system for PMLSM, and some experimental results are confirmed theoretically.
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