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对一类控制方向未知的时变非线性系统的控制问题进行了研究.首先,设计了一种迭代神经网络估计器,并通过推导得到了逼近引理,实现了对时变不确定性的逼近;然后,提出了用迭代神经网络逼近时变不确定性,用Nussbaum函数估计未知控制方向的总体设计思想.利用李雅普诺夫稳定性理论和自适应迭代学习控制技术设计了控制系统,并进行稳定性分析,得到了稳定性定理,解决了这类系统的控制问题.仿真结果验证了控制系统设计方法的正确性.
The control problem of a class of time-varying nonlinear systems with unknown control direction is studied.Firstly, an iterative neural network estimator is designed, and the approximation lemma is deduced to realize the approximation of the time-varying uncertainties Then, the general design idea that the iterative neural network approaches the time-varying uncertainty and the Nussbaum function is used to estimate the unknown control direction is proposed. The control system is designed with the Lyapunov stability theory and the adaptive iterative learning control technique The stability theorem is obtained to solve the control problem of this kind of system, and the simulation results verify the correctness of the control system design method.