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针对一类具有未建模动态和动态扰动且状态不可量测的非线性系统,利用神经网络逼近未知函数设计K-滤波器重构系统状态,提出一种自适应输出反馈控制策略.通过对未建模动态的新刻画,避免动态信号的引入.采用动态面设计方法,取消理论分析中产生的未知连续函数的估计,降低设计的复杂性.利用Lyapunov方法证明了闭环系统的所有信号是半全局一致终结有界的,并通过仿真结果验证了所提出方案的有效性.
Aiming at a class of nonlinear systems with unmodeled dynamic and dynamic perturbations and unmeasurable states, an adaptive output feedback control strategy is proposed by using K-filter to reconstruct the state of the system by using neural network approximation to unknown functions. Modeling dynamic new features to avoid the introduction of dynamic signals.Using dynamic surface design method to cancel the estimation of unknown continuous functions in theoretical analysis and reduce the complexity of the design.The Lyapunov method is used to prove that all the signals of the closed-loop system are semi-global The results are consistent and bounded, and the validity of the proposed scheme is verified by simulation results.