Robust extrapolation for systems with unknown input and interval uncertainty in system and observations V. I. Smagin, K. S. Kim
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ArticleContent type: Текст Media type: электронный Other title: Робастная экстраполяция для систем с неизвестным входом и интервальной неопределенностью в объекте и наблюдениях [Parallel title]Subject(s): надежная экстраполяция | непараметрическое сглаживание | вероятностный подход | системы управления с неполной информациейGenre/Form: статьи в журналах Online resources: Click here to access online
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Вестник Томского государственного университета. Управление, вычислительная техника и информатика № 62. P. 85-91Abstract: The problem of robust extrapolation for discrete linear system with unknown input and uncertain interval parameters in system and model of observations is considered. The probabilistic approach is used, which is based on replacing uncertain parameters of interval type by independent random variables with uniform distribution in recursive Kalman schemes. The LSM algorithms and nonparametric smoothing procedures are applied for estimating unknown input. The proposed algorithms can be used in control systems with incomplete information. Simulation results are presented and discussed.
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The problem of robust extrapolation for discrete linear system with unknown input and uncertain interval parameters in system and model of observations is considered. The probabilistic approach is used, which is based on replacing uncertain parameters of interval type by independent random variables with uniform distribution in recursive Kalman schemes. The LSM algorithms and nonparametric smoothing procedures are applied for estimating unknown input. The proposed algorithms can be used in control systems with incomplete information. Simulation results are presented and discussed.
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