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利用Lyapunov方法 ,提出了一种不确定性机器人系统的自适应鲁棒迭代学习控制策略 ,整个系统在迭代域里是全局渐近稳定的 .所考虑的机器人系统同时包含了结构和非结构不确定性 .在设计时 ,系统的不确定性被分解成可重复性和非重复性两部分 ,并考虑了系统的标称模型 .在所提出的控制策略中 ,自适应策略用来估算做法确定性的界 ,界的修正与迭代学习控制量一样的迭代域得以实现的 .计算机仿真表明本文提出的控制策略是有效的 .
Using Lyapunov method, an adaptive robust iterative learning control strategy for an uncertain robot system is proposed. The whole system is globally asymptotically stable in the iterative domain. The considered robotic system contains both structural and unstructured uncertainties In the design, the system uncertainty is decomposed into two parts: repeatability and non-repeatability, and the nominal model of the system is considered.In the proposed control strategy, the adaptive strategy is used to estimate the method certainty The boundary and the iteration domain of iterative learning control can be realized.Computer simulation shows that the proposed control strategy is effective.