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针对一类具有未知时变时滞的一阶非线性参数化系统,提出一种自适应迭代学习控制方案。通过利用边界层函数构造广义跟踪误差,消除了迭代学习控制初始精确定位的限制。为避免因引入边界层函数而产生的奇异性问题,引入双曲正切函数,并根据双曲正切函数的性质,通过构造Lyapunov-krasovskii型复合能量函数证明了所有信号的有界性和跟踪误差的收敛性。仿真算例验证了所提出方案的有效性。
For a class of first-order nonlinear parameterized systems with unknown time-varying delay, an adaptive iterative learning control scheme is proposed. By using the boundary layer function to construct the generalized tracking error, the limitation of initial precision positioning of iterative learning control is eliminated. In order to avoid the singularity problem caused by the introduction of boundary layer functions, the hyperbolic tangent function is introduced and the boundedness and tracking error of all signals are proved by constructing the Lyapunov-krasovskii complex energy function according to the properties of hyperbolic tangent function Convergence. The simulation example verifies the validity of the proposed scheme.