电液伺服结构试验系统的神经网络快速鲁棒跟踪控制*

针对结构试验系统的非线性和不确定性特性，提出一种神经网络并行自学习跟踪控制器，在满足试验系统实时性要求的条件下，通过神经网络在线建模和虚拟学习做到了控制器的在线自适应设计，并解决了实时训练样本不足的问题，实例仿真表明设计的控制系统具有良好的波形再现能力

Neural Network Based Fast and Robust Tracking Control for Electro-Hydraulic Servo Structural Testing System

A parallel self learning tracking controller based on neural networks,with respect to the complex nonlinearities and uncertainties of structural testing system,is presented in this paper.By introducing a neural network to model the controlled system and using virtual learning,the controller can be adaptively designed on line with no need of the real time measured training data.Meantime,the real time processing ability of the neural network control for complex systems is assured.Simulation results of a real control system show it has good tracking ability.;