永磁直线同步伺服系统混合递归模糊神经网络控制

针对直线电机易受诸多不确定因素的影响，提出了采用递归模糊神经网络和扰动观测器的控制方案。系统采用IP位置控制器；扰动观测器将所观测的扰动力前馈，提高了系统的抗干扰能力。为改善系统受到突加减扰动时的伺服性能，引进了递归模糊神经网络补偿器，采用动态反馈学习算法，在线调整。仿真结果表明，该控制方案可以有效增强系统的鲁棒性。

Hybrid Recurrent Fuzzy Neural Network Controller for Permanent Magnet Linear Synchronous Motor Servo System

This paper present a hybrid controller realized by recurrent fuzzy neural network and disturbance observer. A IP postion controller is adopted. A disturbance observer is implemented and the observed disturbance force is fed forward to increase the robustness of the system. Moreover, to improve the servo performance of system under the occurrence of large disturbance, the recurrent fuzzy neural network compensator is introduced to reduce the influence of parameter variations and external disturbances of the system. The RFNN is trained on line by back propagation algorithm. The results of simulation show that the proposed control method can increase the robustness of system effectively.