机构地区: 北京理工大学自动控制系
出 处: 《吉首大学学报》 1996年第4期37-42,共6页
摘 要: 本文主要从理论上研究神经网络控制器实现SISO离散时间非线性系统的轨迹跟踪问题,在反向传播算法的基础上,提出了一种新的神经网络训练方法,该算法可以直接估计出动态系统所需要的前馈控制,并在一定条件下证明了此神经网络控制系统的稳定性,另外还给出了将其应用于几个不同非线性系统的仿真结果。 This paper investigates neural network controllers to achieve output tracking for a class of discrete-time nonlinear systems. A control strategy is introducted by means of employing the neural networks for direct on-line estimation of the required feedforward control input.The parameters of the networks are updated according to a modified back propagation algorithm under appropriate conditions the stability of the neural network control system is rigorously analyzed. Simulation results reveal that the neural network control scheme suggested here is practically feasible.