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Avtomatika i Telemekhanika, 2017, Issue 10, Pages 55–73
(Mi at14902)
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This article is cited in 2 scientific papers (total in 2 papers)
Nonlinear Systems
Adaptive suboptimal tracking under bounded Lipshitz uncertainty in a discrete minimum-phase object
V. F. Sokolov Komi Research Center of the Ural Branch of the Russian Academy of Sciences, Syktyvkar, Russia
Abstract:
We consider a deterministic problem of asymptotically suboptimal tracking of a bounded reference signal with the output of a scalar discrete minimum-phase object with unknown transition function under a bounded external disturbance and bounded nonlinear stationary uncertainty satisfying a generalized Lipschitz condition. Suboptimality of the tracking is achieved with online estimation and compensation for nonparametric Lipschitz uncertainty in addition to estimating an unknown transition function. To solve the problem we use two parallel estimation algorithms, one of which provides stability for the closed adaptive system, the other, asymptotic tracking optimality with desired accuracy.
Keywords:
adaptive control, suboptimal tracking, Lipschitz uncertainty, model verification, bounded disturbance.
Citation:
V. F. Sokolov, “Adaptive suboptimal tracking under bounded Lipshitz uncertainty in a discrete minimum-phase object”, Avtomat. i Telemekh., 2017, no. 10, 55–73; Autom. Remote Control, 78:10 (2017), 1775–1789
Linking options:
https://www.mathnet.ru/eng/at14902 https://www.mathnet.ru/eng/at/y2017/i10/p55
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Statistics & downloads: |
Abstract page: | 166 | Full-text PDF : | 47 | References: | 48 | First page: | 13 |
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