【作者】 钱厚斌； 张天平；

【Author】 Qian Hou-bin~(1,2),Zhang Tian-ping~1 1.College of Information Engineering;2.Coll.of Journalism & Communication.,Yangzhou University,Yangzhou 225009,China 1.College of Information Engineering,Yangzhou University,Yangzhou 225009,China

【机构】 扬州大学信息工程学院； 扬州大学新闻与传媒学院；

【摘要】 针对一类具有死区模型并且函数控制增益符号未知的不确定SISO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,同时也放宽了时滞不确定项的要求.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.更多还原

【Abstract】 A design scheme of adaptive neural controller for a class of uncertain SISO nonlinear time-varying delay systems with unknown nonlinear dead-zones and unknown function control gain is proposed.The design is 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 and the supposition further broadness to unknown function.The unknown time-varying delay uncertainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design.By theoretical analysis,the closed-loop control systems is proved to be semi-globally uniformly ultimately bounded.Simulation results demonstrate the effectiveness of the approach.更多还原