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针对一类具有输入及状态未建模动态的非线性系统,设计K滤波器来估计系统不可量测状态,基于动态面控制技术并利用径向基函数神经网络的逼近能力,提出一种输出反馈自适应跟踪控制方案.利用Nussbaum函数性质,有效地解决了高频增益符号未知问题.在控制器设计中引入规范化信号来约束输入未建模动态,从而有效地抑制其产生的扰动.通过理论分析证明了闭环控制系统是半全局一致终结有界的.
For a class of nonlinear systems with input and state unmodeled dynamics, K filter is designed to estimate the unmeasured state of the system. Based on the dynamic surface control technique and the approximation ability of radial basis function neural network, an output feedback Adaptive tracking control scheme.Using the nature of Nussbaum function, the problem of unknown sign of high-frequency gain is effectively solved.The normalized signal is introduced into the controller design to restrain the unmodeled dynamic input, thus effectively suppressing the disturbance caused by it.According to the theoretical analysis It is proved that the closed-loop control system is semi-globally uniformly terminated.