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针对一类具有未建模动态和输出约束的输出反馈非线性系统,提出一种自适应输出反馈动态面控制方案.利用神经网络逼近未知连续函数,分别设计K滤波器和动态信号估计不可测量的状态,并处理动态不确定性.引入障碍李雅普诺夫函数并设计自适应控制器以保证BLF有界,从而实现输出约束.理论分析表明,闭环控制系统是半全局一致终结有界的,且满足输出约束,仿真结果验证了所提出方案的有效性.
Aiming at a class of output feedback nonlinear systems with unmodeled dynamics and output constraints, an adaptive output feedback dynamic surface control scheme is proposed. By using neural networks to approximate unknown continuous functions, K filters and dynamic signals are estimated to be unmeasurable State and deal with the dynamic uncertainty.An obstruction Lyapunov function is introduced and an adaptive controller is designed to ensure that the BLF has a boundedness so as to achieve the output constraint.Theoretical analysis shows that the closed-loop control system is semi-globally uniformly terminated and satisfies Output constraints, the simulation results verify the effectiveness of the proposed scheme.