Model reference adaptive fuzzy neural network control based speed servo system of linear permanent magnet synchronous motor

Abstract: Accounting for the closed-loop control system of linear permanent magnet synchronous motor is apt to be disturbed. It is the main problem which can degrade the performance of the control system and even destabilize the system. Presenting an on-line identification method of model reference adaptive control based on fuzzy neural network on the paper. And the inputs and membership parameters of the fuzzy controller are modified in real-time by a gradient method. It is proved that the method above is valid for improving the resolving of velocity detects device and dynamic response by simulation and practice. And the system is robust.