基于改进的径向基函数神经网络混合控制在电液伺服系统中的应用  

Hybrid Control Based on Improved Radial Basis Function Network for Electro-hydraulic Servo System

作　　者：杨逢瑜[1] 娄磊[1] 王顺[1] 陈君辉[1] 王其磊[1] 

机构地区：[1]兰州理工大学流体动力与控制学院,甘肃兰州730050

出　　处：《机床与液压》2009年第9期187-189,共3页Machine Tool & Hydraulics

摘　　要：由于电液伺服系统中存在扰动和干扰,一般的控制器很难在各种条件下都取得良好的输出响应。为了解决此类问题,提出了一种基于改进的RBF神经网络混合控制策略。使用基于群组优化理论的离线优化算法来选择RBF神经网络的隐节点数目,用各种在线学习算法来调节隐节点的中心和估计连接权值。该混合控制器结合了改进的RBF神经网络与传统PID控制的优点,被广泛适用于船舶试验台的电液伺服系统中。试验仿真结果表明,使用这种混合控制器的伺服系统具有良好的动态特性和鲁棒性。Because of the perturbations and disturbances of electro-hydranlic servo systems, the normal controller can＇t obtain good output responses under various conditions. A hybrid control strategy based on improved Radial Basis Function （RBF） network was presented for the tracking problem. An oflline optimization algorithm was employed to choose the number of hidden units of RBF network. Based on the theory of optimization in groups, different online learning algorithms were used to adjust centers and estimate connection weights. The hybrid controller combined this improved RBF network with traditional PID control, and it was applied to electro-hydraulic servo system of ship test bed. Simulation results show that the servo system has good dynamic performance and nice robustness with this hybrid controller.

关 键 词：电液伺服系统 改进的RBF神经网络 混合控制器 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置]