| Title |
A Speed Control of Switched Reluctance Motor using Fuzzy - Neural Network Controller |
| Authors |
박지호 ; 김연충 ; 원충연 ; 김창림 ; 최경호 |
| Abstract |
Switched Reluctance Motor(SRM) have been expanding gradually their applications in the variable speed drives due to their relatively low cost simple and robust structure, controllability and high efficiency. In this paper neural network theory is used to determine fuzzy-neural network controller"s membership functions and fuzzy rules. In addition neural network emulator is used to emulate forward dynamics of SRM and to get error signal at fuzzy-neural controller output layer. Error signal is backpropagated through neural network emulator. The backpropagated error of emulator offers the path which reforms the fuzzy-neural network controller"s membership functions and fuzzy rules. 32bit Digital Signal Processor(TMS320C31) was used to achieve the high speed control and to realize the fuzzy-neural control algorithm. Simulation and experimental results show that in the case of load variation the proposed control method was superior to a conventional method in the respect of speed response. |