受饱和输入约束的非线性系统滑模自适应控制  

Adaptive sliding-mode control for SISO nonlinear systems with input saturation

作　　者：李永刚[1] 李星野[1] 

机构地区：[1]上海理工大学管理学院系统科学与工程系,上海200093

出　　处：《计算机工程与应用》2010年第31期235-238,共4页Computer Engineering and Applications

基　　金：上海市自然科学基金 No.06ZR14144;上海市教育委员会科研项目(No.07ZZ94)~~

摘　　要：利用神经网络和滑模控制,研究带有饱和输入的一类非线性系统。为了便于问题分析,引入饱和约束模型输出与控制输入的差值这个变量,分5种情况讨论,求得神经网络权值的在线调节律,得到保证闭环系统稳定的控制律。利用Lyapunov函数,证明了闭环系统的稳定性;仿真实验说明了算法的有效性。This paper is concerned with a class of SISO nonlinear systems with input saturation,which is studied by sliding mode control and neural networks.A new parameter is introduced as the difference between control input and the output of the input saturation,5 situations are discussed,the weight updating laws of the neural networks are acquired.The control law can stabilize the closed-loop system,the stability of the system is proved by Lyapunov function,the simulation results show the feasibility of this method.

关 键 词：非线性系统 饱和输入 神经网络 滑模控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]