永磁直线同步电动机模糊神经网络控制器的设计

为了有效地抑制负载阻力扰动等外部扰动对永磁直线同步电动机(PMLSM)系统稳态性能影响,本文设计出了模糊神经网络控制器(FNNC).该控制器将模糊控制的非线性辩识功能和神经网络的自学习功能有效地结合了起来,在保留神经网络自学习能力的同时,增加了对系统的辨识能力,从而提高了伺服系统的稳态性能.仿真结果表明,基于FNNC的PMLSM伺服系统响应快,精度高,对外部扰动有很强的鲁棒性.

Fuzzy Neural Network Controller Design for Permanent Magnet Linear Synchronous Motor

Fuzzy neural network controller(FNNC) is designed to aim at the effect caused by the outside disturbance for the steady-state performance of permanent magnet linear synchronous motor(PMLSM) servo system. The FNNC combines the non-linear identification of fuzzy control with self-learning of neural network. It can reserve the self-learning abilities, improve the identification ability for servo system and then enhance the steady-state performance of PMLSM. The simulation results show that the servo system for PMLSM based on FNNC can realize quick response, high precision and strong robustness for the outside disturbance.