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Iterative Learning Control for Discrete Singular Systems with Randomly Varying Trial Lengths

机译:具有随机变化的试用长度的离散奇异系统的迭代学习控制

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This paper researches iterative learning control for a class of singular systems with randomly iteration varying lengths. Based on an equivalence decomposition of discrete singular systems, a new learning algorithm with a stochastic variable and moving average operator is used to cope with the state tracking problem under non-uniform trial lengths circumstance. The stochastic variable is included both in tracking error and control input. Furthermore, the convergence condition of the proposed learning scheme is put forward and strictly proved. In the end, a numerical example is presented to demonstrate the effectiveness of the theoretical results.
机译:本文研究了一类具有随机迭代变化长度的奇异系统的迭代学习控制。在离散奇异系统的等价分解的基础上,采用具有随机变量和移动平均算子的新学习算法来应对非均匀试验长度情况下的状态跟踪问题。随机变量包括在跟踪误差和控制输入中。此外,提出并严格证明了所提出学习方案的收敛条件。最后,通过数值例子说明了理论结果的有效性。

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