时滞系统的神经网络辨识与控制算法  

Identification and Control of Systems with Time Delay Using Neural Networks

作　　者：杨林[1] 任雪梅[1] 黄鸿[1] 张兴华[1] 

机构地区：[1]北京理工大学自动控制系,北京100081

出　　处：《计算技术与自动化》2006年第3期9-12,共4页Computing Technology and Automation

基　　金：国家自然科学基金资助项目(60474033)

摘　　要：针对时滞系统、应用神经网络的非线性逼近能力,采用神经网络实现内模控制中被控对象的正模型及内模控制器,用Lyapunov稳定性定理证明神经网络控制系统的稳定性。仿真结果说明神经网络内模控制方案的优越性。Considering the nonlinear approximation ability of neural networks, this paper presents the identification model and controller based on neural networks for systems with time delay, The neural networks are used to implement the plant model and internal model controller. The stability of the neural network control system is proved by Lyapunov theory. Simulation results demonstrate the advantages of the proposed neural network internal model control scheme.

关 键 词：时滞系统 内模控制 神经网络 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]