Algorithms of Sustainable Estimation of Unknown Input Signals in Control Systems

• Autorzy: Yusupbekov Nadirbek , Igamberdiev Husan , Mamirov Uktam

Identyfikatory

DOI

10.14313/JAMRIS_4-2018/29

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

control system; state; signal reconstruction; regularization; regularization parameter

PL

układ sterowania; stan; rekonstrukcja sygnału; regularyzacja; parametr regularyzacji

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2018
• Tom: Vol. 12, No. 4
• Strony: 83--86
• Opis fizyczny: Bibliogr. 18 poz., rys.

Twórcy

autor

Yusupbekov Nadirbek

• Department of Automation of Production Processes, Tashkent State Technical University, Tashkent, Republic of Uzbekistan

autor

Igamberdiev Husan

• Department Information processing and control systems, Tashkent State Technical University, Tashkent, Republic of Uzbekistan

autor

Mamirov Uktam

• Department of Information processing and management system, Tashkent State Technical University, Tashkent, Republic of Uzbekistan

Bibliografia

• [1] M.A. Ogarkov, “Methods of statistical estimation of parameters of stochastic processes”, Energoatomizdat, 1990.
• [2] N.T. Kuzovkov, O.S. Silychev, “Inertial navigation and optimal filtration,” Mashinostroenie, 1982.
• [3] A.A. Vengerov, V.A. Shcharensky, “Applied questions of optimal linear filtration,” Energoizdat, 1982.
• [4] V. Strejc, State space theory of discrete linear control, John Wiley & Sons, Inc., 1981.
• [5] S.B. Peltsverger, “Algorithmic support of assessment processes in dynamic systems under uncertainty,” Nauka, 2004.
• [6] N.R. Yusupbekov, H.Z. Igamberdiev, O.O. Zaripov, SH.M. Gulyamov, “Regular estimation of dynamic control objects conditions on the basis of adaptive filtering concepts”, In: Proceedings of 9th International Conference on Application of Fuzzy Systems and Soft Computing, Prague, Czech Republic, August 26–27, 2010, 291–299.
• [7] H.Z. Igamberdiev, O.O. Zaripov, “Regularized algorithms for restoring input effects in control systems,” Journal of Automation and Modern Technologies, Moscow, no. 7, 2014, 31–34.
• [8] U.F. Mamirov, O.O. Zaripov “Algorithms of the adaptive estimation in the conditions of uncertainty of the perturbing influences”, International Journal of Advanced Research in Science, Engineering and Technology, India, vol. 3, no. 8, 2016, 2448-2454.
• [9] A.N. Tikhonov, V.J. Arsenin, “The methods of solution of ill-posed problems,” Nauka, 1979.
• [10] A.N. Tikhonov, A. Goncharsky, V.V. Stepanov, A.G. Yagola, Numerical methods for the solution of ill-posed problems, Springer Netherlands, 1995, DOI: 10.1007/978-94-015-8480-7.
• [11] A.N. Tikhonov, A.V. Goncharsky (eds.), Ill-conceived problems of natural science, Publ. Mosk. University, 1987.
• [12] V.A. Morozov, “Regular methods for solving illposed problems,” Nauka, 1987.
• [13] Yu.E. Voskoboinikov, Stable methods and algorithms for parametric identification, Novosibirsk: NSASU (Sibstrin), 2006.
• [14] J.W. Demmel, Applied numerical linear algebra, Society for Industrial and Applied Mathematics, 1997.
• [15] G.H. Golub, C.F. van Loan, Matrix computations, Johns Hopkins University Press, 2012.
• [16] C.L. Lawson, R.J. Hanson, Solving least squares problems, Society for Industrial and Applied Mathematics, 1987.
• [17] A.I. Zhdanov, Introduction to methods for solving ill-posed problems, Samara State Aerospace University, 2006.
• [18] V.A. Morozov, “Algorithmic foundations of methods for solving ill-posed problems,” Vychisl. Metody Programm., vol. 4, no. 1, 2003, 130–141.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).