New P-type and D-type iterative learning control update laws for networked control systems with random data dropouts

Автор: Najafi S.A., Delavarkhalafi A.

Журнал: Вестник Южно-Уральского государственного университета. Серия: Математическое моделирование и программирование @vestnik-susu-mmp

Рубрика: Математическое моделирование

Статья в выпуске: 2 т.13, 2020 года.

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In this paper, we present two new P-type and D-type iterative learning control (ILC) update laws for linear stochastic systems with random data dropout modeled with a Bernoulli random variable. We prove that the P-type and D-type ILC update laws converge to the desired input in the almost sure sense. We show that the convergence conditions of the inputs corresponding to the P-type and D-type ILC update laws for networked control systems are the same. We present the performance comparison of the P-type and D-type ILC update laws. In this comparison, we conclude that the P-type ILC update law is more effective than the D-type ILC update law for networked control systems.

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Iterative learning control, d-type, p-type, data dropout, networked control linear system, d-тип

Короткий адрес: https://sciup.org/147235015

IDR: 147235015 | DOI: 10.14529/mmp200206

Список литературы New P-type and D-type iterative learning control update laws for networked control systems with random data dropouts

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