控制增益符号未知的MIMO时滞系统自适应控制  

Adaptive control of MIMO nonlinear time-varying delay systems with unknown gain signs

作　　者：钱厚斌[1] 张天平[1] 

机构地区：[1]扬州大学信息工程学院,新闻与传媒学院江苏扬州225009

出　　处：《控制与决策》2008年第10期1153-1158,1162,共7页Control and Decision

基　　金：国家自然科学基金项目(60774017);江苏省教育厅自然科学基金项目(07KJB520133)

摘　　要：针对一类带有死区模型并具有未知函数控制增益的不确定MIMO非线性时滞系统,基于滑模控制原理和Nussbaum函数的性质,提出了一种稳定的自适应神经网络控制方案.该方案放宽了对函数控制增益上界为未知常数的假设,并通过使用Lyapunov-Krasovskii泛函抵消了因未知时变时滞带来的系统不确定性.理论分析证明,闭环系统是半全局一致终结有界.仿真结果表明了该方法的有效性.A design scheme of adaptive neural controller for a class of uncertain MIMO nonlinear time-varying delay systems with unknown nonlinear dead-zones and unknown function control gain is proposed, based on the principle of sliding mode control and property of Nussbaum-type functions. The approach relaxes the hypothesis that the upper bound of function control gain is unknown constant. The unknown time-varying delay uncertainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. By using theoretical analysis, the closed-loop control systems is proved to be semi-globally uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the approach.

关 键 词：自适应控制 神经网络 滑模控制 时变时滞 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]