基于滑模和神经网络的永磁直线伺服系统控制

针对直接驱动的交流永磁直线伺服系统，提出一种将非线性神经网络控制和滑模控制相结合构成的双自由度控制策略，该控制策略解决了直线伺服系统跟踪性能和鲁棒性能之间的矛盾，滑模输入控制器保证了系统对给定的快速跟踪性能；神经网络输出反馈控制器对系统参数变化和阻力扰动（包括直线电机的端部效应力）进行很大程度的抑制，并可以削弱滑模控制的抖振对系统稳态性能的影响，仿真结果表明该方案在保证伺服系统的快速性同时，对系统参数变化和阻力扰动具有很强的鲁棒性。

Permanent magnet linear servo system control based on neural network and sliding

A dual degree of freedom control scheme based on combining nonlinear neural network (NN) control and sliding mode control for a direct drive AC permanent magnet linear servo system is presented in this paper. The sliding mode input controller ensure the system has fast tracking characteristic to the command signal. While the neural network output feedback controller suppress parameter variations and resistance perturbation( including the end effect force produced by of linear motor) greatly, and can effectively minimize the chattering of sliding mode control which could influence the steady state performance of the system. Some simulation results show that this control scheme can not only enhance the track command ability and the robustness of the linear servo system, but also has strong robustness to parameter variations and resistance perturbation.