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Robustness Analysis of Open-closed-loop D-type Iterative Learning Control Algorithm for Nonlinear Systems with Deviations on Initial State

机译:初始状态偏差偏差偏离闭环D型迭代学习控制算法的鲁棒性分析

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This paper discusses the robustness of a class of non-linear system with Open-closed-loop D-type iterative learning control (ILC) algorithm under the condition of having initial state errors, when the system reaches the convergence condition. The theory analysis indicates, when initial state errors were bounded, the ILC scheme is robust The control error will converge to some neighborhood of desired control value, whose breadth is associated with the disturbance bound during the operation of nearly two iterative learning and not associated with initial control input. We can conclude that the system will reach desired value more closely when the system has less disturbance.
机译:本文讨论了在系统达到收敛条件时具有初始状态误差的条件下具有开闭环D型迭代学习控制(ILC)算法的一类非线性系统的鲁棒性。 理论分析表明,当初始状态误差有界时,ILC方案稳健,控制误差将收敛到所需控制值的一些邻域,其宽度与近两个迭代学习期间的干扰绑定相关联的扰动相关联 初始控制输入。 我们可以得出结论,当系统具有较小的干扰时,系统将更加触及所需的值。

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