신경회로망을 이용한 SRM의 토오크 제어

Torque Control Scheme of Switched Reluctance Motor using Neural Network

The torque of SRM is developed by phase currents and inductance variation. Phase currents and inductance variation. Phase current is often the controlled variable in electrical motor drives, so it seems natural to use closed loop current controllers. However, the highly nonlinear nature of switched reluctance motors makes optimisation of closed loop current controlled difficult because of saturation effect in magnetic circuit. Therefore, torque generation region is nonlinearly varied according to phase current and rotor position. This paper describes the torque control scheme with neural network that can control varied with load torque. The torque control is simulated by PSIM.