| Title |
Maximum Torque Control of IPMSM with Adaptive Learning Fuzzy-Neural Network |
| Authors |
Jae-Sub Ko ; Jung-Sik Choi ; Dong-Hwa Chung |
| Keywords |
IPMSM Drive ; Maximum torque control ; Fuzzy neural network ; Artifidal neural network ; Speed estimation ; Speed control |
| Abstract |
Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter"s current and voltage rated value. This paper proposes speed control of IPMSM using adaptive learning fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive learning fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive learning fuzzy neural network and artificial neural network. |