Iterative learning control for conformable stochastic impulsive differential systems with randomly varying trial lengths

IF 1.4 4区 工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY International Journal of Nonlinear Sciences and Numerical Simulation Pub Date : 2022-10-06 DOI:10.1515/ijnsns-2021-0382
Wanzheng Qiu, Michal Feckan, Jinrong Wang, D. Shen
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Abstract

Abstract In this paper, we introduce a new kind of conformable stochastic impulsive differential systems (CSIDS) involving discrete distribution of Bernoulli. For random discontinuous trajectories, we modify the tracking error of piecewise continuous variables by a zero-order holder. First, the improved P-type and PD α -type learning laws of the random iterative learning control (ILC) scheme are designed through global and local averaging operators. Next, we establish sufficient conditions for convergence of the tracking error in the expectation sense and prove the main results by using the impulsive Gronwall inequality and mathematical analysis tools. Finally, the theoretical results are verified by two numerical examples, and the tracking performance is compared for different conformable order of α.
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试验长度随机变化的适形随机脉冲微分系统的迭代学习控制
摘要本文引入了一类涉及伯努利离散分布的新的可调随机脉冲微分系统(CSIDS)。对于随机不连续轨迹,我们用零阶保持器修正了分段连续变量的跟踪误差。首先,通过全局和局部平均算子设计改进的随机迭代学习控制(ILC)方案的p型和PD α型学习律;其次,我们建立了期望意义下跟踪误差收敛的充分条件,并利用脉冲Gronwall不等式和数学分析工具证明了主要结果。最后,通过两个数值算例验证了理论结果,并比较了不同α符合阶数下的跟踪性能。
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来源期刊
CiteScore
2.80
自引率
6.70%
发文量
117
审稿时长
13.7 months
期刊介绍: The International Journal of Nonlinear Sciences and Numerical Simulation publishes original papers on all subjects relevant to nonlinear sciences and numerical simulation. The journal is directed at Researchers in Nonlinear Sciences, Engineers, and Computational Scientists, Economists, and others, who either study the nature of nonlinear problems or conduct numerical simulations of nonlinear problems.
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