基于非线性反馈函数,文章设计神经网络状态观测器,解决一类非线性系统的输出反馈控制问题.非线性反馈神经网络观测器在系统存在不确定性函数的情况下实时估计系统状态.利用所获得的状态信号,设计了自适应神经网络动态面控制器,同时保证了闭环系统的稳定性和所有信号的有界性.通过调节设计参数的取值能够达到期望的闭环跟踪性能.数值仿真表明,所设计的状态观测器不需要对原系统做状态变换,能够克服输出反馈滑模控制器带来的抖震问题.%Based on nonlinear feedback function, this paper investigates output feedback control problem for a class of nonlinear systems. In the case of systems with uncertain functions, nonlinear feedback neural network observer estimates system states in real time. Employing the obtained state signals, an adaptive neural network controller is designed to guarantee the stability of the closed-loop system and the boundedness of all signals. The desired closed-loop tracking performance can be achieved by adjusting the value of the design parameters. Numerical simulation results show that, without state transformation, the state observer overcomes the chattering problem caused by the output feedback sliding mode controller.
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