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Algorithms of Sustainable Estimation of Unknown Input Signals in Control Systems

Yusupbekov Nadirbek, Igamberdiev Husan, Mamirov Uktam

Journal of Automation Mobile Robotics and Intelligent Systems

2018

Vol. 12, No. 4

83--86

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.