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Algorithms of Sustainable Estimation of Unknown Input Signals in Control Systems
Nadirbek Yusupbekov, Husan Igamberdiev and Uktam Mamirov

The problem of estimating unknown input effects in control systems based on the methods of the theory of optimal dynamic filtering and the principle of expansion of mathematical models is considered. Equations of dynamics and observations of an extended dynamical system are obtained. Algorithms for estimating input signals based on regularization and singular expansion methods are given. The above estimation algorithms provide a certain roughness of the filter parameters to various violations of the conditions of model problems, i.e. are not very sensitive to changes in the a priori data.

Keywords: Control system, state, signal reconstruction, regularization, regularization parameter

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