非线性离散系统迭代变持续时间下的开闭环迭代学习控制

Yun‐Shan Wei, Jiaxuan Wang, Jin‐Fan Wang
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引用次数: 0

摘要

针对非线性离散多输入多输出(MIMO)系统,提出了一种迭代变时长下的开闭环迭代学习控制方案。提出了改进的带反馈控制的p型ILC律,以补偿由于迭代持续时间的变化而导致的先前迭代所丢失的跟踪信息。证明了当初始状态期望与参考状态期望相同时,在数学期望意义上ILC跟踪误差可以被驱动到零。最后,通过仿真算例验证了所提ILC律的有效性。
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Open-Closed-Loop Iterative Learning Control for Non-linear Discrete-time Systems under Iterative Varying Duration
This article presents an open-closed-loop iterative learning control (ILC) scheme for non-linear discrete-time multiple-input multiple-output (MIMO) systems under iterative varying duration. The improved P-type ILC law with feedback control is presented to compensate the missing tracking information of the previous iterations due to the iterative varying duration. It is proved that when the initial state expectation is identical to the reference sate, ILC tracking error can be driven to zero in mathematical expectation sense. Finally, a numerical example of simulation is provided to verify the validity of the proposed ILC law.
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