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High-order PD~α-Type Iterative Learning Control and its Lebesgue-p Norm Convergence

机译:高阶PD〜α型迭代学习控制及其LEBESGUE-P常规收敛

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This paper investigates a high-order PD~α - type iterative learning control strategy for a class of fractional-order linear time-invariant systems with Caputo derivative 0<α<1. On the basis of fractional integration by parts and generalized Young inequality, sufficient convergence condition of the learning control law is established in the sense of Lebesgue-p norm. It is shown that the convergence condition is not only dependent on the fractional-order derivative learning gains, along with the system order, but also dependent on the proportional learning gains and all the matrices associated with the system. Finally, a mumerical example is given to demonstrate the validity of the proposed control law.
机译:本文研究了一类分数级线性时间不变系统的高阶PD〜α型迭代学习控制策略,具有Caputo衍生物0 <α<1。在按零件和广义年轻不平等的分数整合的基础上,在Lebesgue-P符号的意义上建立了学习控制法的充分收敛条件。结果表明,收敛条件不仅取决于分数阶衍生学习收益,以及系统顺序,还取决于比例学习收益和与系统相关联的所有矩阵。最后,给出了一种言语例证证明了所提出的控制法的有效性。

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