Uktam
@tdtu.uz
Department of "Information Processing and Management Systems"
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Husan Igamberdiev, Uktam Mamirov, and Shukhrat Tulyaganov
Springer Nature Switzerland
H. Z. Igamberdiev, A. N. Yusupbekov, U. F. Mamirov, and Sh. D. Tulyaganov
Springer Nature Switzerland
H Z Igamberdiev, H I Sotvoldiyev, and U F Mamirov
IOP Publishing
Abstract The paper considers the issues of constructing stable control algorithms for non-stationary objects based on the concepts of game methods. According to the principle of dynamic programming, control is defined when there are or are no restrictions on control actions. A.N.Tikhonov’s regularization method is used for stable estimation of the perturbation vector using the principle of the least residual estimate, as well as the method for compiling and solving an extended regularized normal system of equations. The obtained expressions make it possible to form control algorithms for linear non-stationary objects, which are stable when the control actions are limited, taking into account the feedback channel signal. At the same time, the use of game theory methods makes it possible to optimize management decisions under the conditions of inefficiency of classical management methods under conditions of a high level of a priori uncertainty of processes in the system under consideration.
Husan Igamberdiev, Azizbek Yusupbekov, Uktam Mamirov, and Inomjon Abdukaxxarov
Springer International Publishing
Nodirbek Yusupbekov, Husan Igamberdiev, and Uktam Mamirov
Springer International Publishing
N. R. Yusupbekov, H. Z. Igamberdiev, O. O. Zaripov, and U. F. Mamirov
Springer International Publishing
A. N. Yusupbekov, J. U. Sevinov, U. F. Mamirov, and T. V. Botirov
Springer International Publishing
H. Z. Igamberdiev and U. F. Mamirov
Springer International Publishing
Nadirbek Yusupbekov, Husan Igamberdiev, and Uktam Mamirov
PIAP - Industrial Research Institute for Automation and Measurements
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.