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An iterative learning control algorithm based on time varying pilot factor

机译:一种基于时变导频率的迭代学习控制算法

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Owing to the control system being repetitive and nonlinear, a time-varying pilot factor control algorithm based on iterative learning control is proposed. The convergence of the TPF-ILC control algorithm is mathematically proven and the sufficient conditions are given. Thereafter, the initial state issue of iterative learning is explored, which is the critical issue of iterative learning control. The convergence of the system's control error and the initial state of every single period have been mathematically proved by using continuous and repetitive properties of the system, even if the initial states of every single iterative learning period are not strictly the same. At the end of this paper, the TPF-ILC algorithm is applied in a hydraulic servo control system, and experimental results indicate the effectiveness and practicability of the TPF-ILC algorithm.
机译:由于控制系统是重复和非线性的,提出了一种基于迭代学习控制的时变导频因子控制算法。 TPF-ILC控制算法的收敛在数学上被证明,并且给出了足够的条件。 此后,探讨了迭代学习的初始州问题,这是迭代学习控制的关键问题。 通过使用系统的连续和重复属性,系统的控制误差和每个单个时段的初始状态的收敛也是通过系统的连续和重复的性质来证明,即使每个单个迭代学习期的初始状态并不严格相同。 在本文的末尾,TPF-ILC算法应用于液压伺服控制系统,实验结果表明TPF-ILC算法的有效性和实用性。

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