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High-Order Feedback Iterative Learning Control Algorithm with Forgetting Factor

机译:具有遗忘因子的高阶反馈迭代学习控制算法

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摘要

A novel iterative learning control (ILC) algorithm is proposed to produce output curves that pass close to the desired trajectory. The key advantage of the proposed algorithm is introducing forgetting factor, which is a function of the number of iterations. Due to the forgetting factor characteristic of ILC, the proposed scheme not only stabilizes the nonlinear system with uncertainties but also weakens interference on the tracking desired trajectory. Simulation examples are included to demonstrate feasibility and effectiveness of the proposed algorithm.
机译:提出了一种新颖的迭代学习控制(ILC)算法,以产生通过所需轨迹的输出曲线。所提出算法的主要优点是引入了遗忘因子,该因子是迭代次数的函数。由于ILC的遗忘因子特性,所提出的方案不仅稳定了具有不确定性的非线性系统,而且减弱了对跟踪期望轨迹的干扰。包括仿真示例,以证明所提算法的可行性和有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第21期|826409.1-826409.7|共7页
  • 作者单位

    Yanshan Univ, Dept Elect Engn, Qinhuangdao 066004, Peoples R China;

    Yanshan Univ, Dept Elect Engn, Qinhuangdao 066004, Peoples R China;

    Yanshan Univ, Dept Elect Engn, Qinhuangdao 066004, Peoples R China;

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