Regularized algorithms of adaptive assessment of state of control objects with parametric perturbation account

Authors

Х.Z Igamberdiyev, Academician of the Academy of Sciences of the Republic of Uzbekistan, Doctor of Technical Sciences, Professor, Department of Information Processing and Control Systems, Tashkent State Technical University;
D.T Kadirov, Junior Researcher, Tashkent State Technical University, Tel .: (94) 605-36-22Follow

Abstract

The problems of constructing stable algorithms for adaptive estimation of the state of control objects with allowance for parametric perturbations based on the theory of conditional Gaussian filtration are considered. Algorithms for estimating the state of stochastic controllable objects using the regularized method of the Cholesky factorization and pseudo-inversion of perturbed symmetric matrices are given. These algorithms allow us to stabilize the procedure for inversion of matrices in estimating the state of stochastic objects and, thereby, to increase the accuracy of determining the true estimate of the state vector when the parameters of the object and the observer are perturbed.

First Page

47

Last Page

51

References

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Recommended Citation

Igamberdiyev, Х.Z and Kadirov, D.T (2018) "Regularized algorithms of adaptive assessment of state of control objects with parametric perturbation account," Chemical Technology, Control and Management: Vol. 2018: Iss. 2, Article 9.
DOI: https://doi.org/10.34920/2018.3.47-51