摘要
针对永磁直线同步电机(PMLSM)直接驱动系统的非线性与电机参数时变、易受扰动的特性,提出一种基于BP神经网络的自适应神经网络速度控制器。该控制器由一个传统的PID位置控制器、神经网络控制器(NNC)和神经网络辨识器(NNM)组成。仿真结果表明,当突加负载扰动或参数突变时,系统具有较好的动态性能和较强的鲁棒性,能够满足工业场合高精度、微进给的需求。
An adaptive neural network control system was proposed to control the speed of the mover of a permanent magnet linear synchronous motor （PMLSM） servo drive system considering nonlinear and parame- ters time-variation. The controller is composed of a conventional PID position controller, a neural network controller （NNC） and a neural network module （NNM）. The simulation results show that the proposed controller has superior dynamic stability and strong robustness , when the loads or parameters are suddenly increased or decreased, and the drive system can satisfy the need of high precision and micro-feed.
出处
《电气传动》
北大核心
2008年第6期37-39,共3页
Electric Drive
关键词
自适应神经网络
永磁直线同步电机
速度控制
adaptive neural network
permanent magnet linear synchronous motor（PMLSM）
speed control
