【摘要】 针对电液伺服系统的复杂非线性和不确定性特性，提出一种基于神经网络的在线自学习自适应控制策略，引入的神经网络模型可跟踪学习系统的时变动力学，控制器的设计不依赖于系统的先验知识，控制参数的调整是基于被控过程的测量信息利用反馈误差学习算法来实现的。该系统已应用于大型电液伺服结构试验机的控制，显示了优良的控制品质。更多还原

【Abstract】 A neural network based on line self learning adaptive control strategy is presented with respect to the complex nonlinearities and uncertainties of electro hydraulic servo system.A neural network model is introduced to learn the nonlinear and time varying dynamics of the controlled plant.The controller can be designed with no prior information required about the controlled plant,and the control parameters can be regulated on line by using the measured input/output data with feedback error learning method.It is applied to the control of an electro hydraulic servo strcutrual testing system.The tracking results show that the controller has very good control performances.更多还原