ALGORITHMS FOR FORMATION OF CONTROL EFFECTS IN CONDITIONS OF UNOBSERVABLE DISTURBANCES
Creators
- 1. doctor of technical sciences, Associate Professor of the department "Information Processing Systems and Control" at Tashkent state technical university named after Islam Karimov
- 2. senior lecturer of the department "Information Processing Systems and Control" at Tashkent state technical university named after Islam Karimov
Description
this article develops an algorithm for synthesizing a complex-shaped command-tracking system based on modal considerations by compensating for interference signals when there is an effect of unknown unobservable disturbances on the control object. In this case, the control signal is selected in such a way that the output of the object must accurately and inertibly monitor each command signal. By predicting the future character of the object when the state of the system can be measured directly, we can ensure the observation of command signals using linear feedback to the state.Using Cauchy's formula, the matrix obtained by zeroing the co-head due to the galaions in the equation representing the exact output of the object is an poor-conditioned matrix. A modified Greville's constructive algorithm was used to determine these pseudo-inverse matrices. The structure of the resulting tracking system is built. Its main elements are the identifier of the command signal, the identifier of the interrupts and the state of the object. If the matrices in the identifiers are selected correctly, the system provides high-precision tracking of command signals even in the presence of any interference.
Files
22_199_123-127 Mamirov Buronov-.pdf
Files
(945.0 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:06fdde2e13c11b773b5514f522998a21
|
945.0 kB | Preview Download |
Additional details
References
- Glad, T., & Ljung, L. (2000). Control Theory (1st ed.). CRC Press. https://doi.org/10.1201/9781315274737.
- Strejc V. State Space Theory of Discrete Linear Control. IEEE Transactions on Systems, Man, and Cybernetics. Publisher: IEEE, 1982
- Simagina. O.V. Control theory: textbook, Novosibirsk: SibAGS publishing house, 2014.-135 p.
- Afanasyev V.N. "Control of indefinite dynamic objects", Moscow, Fizmat-ref, 2008. – 208 p.
- Ogarkov M.A. Methods of statistical estimation of parameters of random processes. Moscow, Energoatomizdat, 1990. 208 p.
- Filtering and stochastic control in dynamic systems. / Ed. K. T. Leondes Trans. from English, - M.: Mir, 1980. - 407 p.
- Pelzverger S.B. Algorithmic support of assessment processes in dynamic systems under conditions of uncertainty. -M.: Nauka, 2004. - 116 p.
- Mamirov U.F. Regular synthesis of adaptive control systems for uncertain dynamic objects. – Tashkent: Publishing house. "Knowledge and intellectual potential", 2021. –215 p.
- Karabutov N.N. Structural identification of static objects. -Librocom. 2011 -152 p.
- Mamirov U.F., Azamkhonov B.S. Algorithms for stable estimation of parameters and state of nonlinear control objects // Scientific-technical journal (STJ FerPI, FarPI ITZh, NTZh FerPI, 2020, T.24, special issue No. 1). –P.274-278.
- Kisenkova N.A., Joint estimation of object parameters and statistical characteristics of non-Gaussian disturbances, Avtomat. and Telemekh., 1991, issue 11, 71–80.
- Mamirov U.F., Buronov B.M. Systematic analysis of methods of control of dynamic objects in conditions of non-measurable disturbances // Chemical technology control and management. 2023, No. 4 (112) pp.49-63.
- Igamberdiev Kh.Z., Kholkhodzhaev B.A., Mamirov U.F. Formation of stable algorithms for estimating unknown input signals in dynamic control systems // Journal of Technical Sciences and Innovation. Tashkent. 2019. No. 1. -WITH. 63-67.
- F.R.Gantmaher, "Matrix theory", Moskva, Nauka, 1988, 552 p.
- James W., Demmel, "Applied numerical linear algebra", Berkeley, California, University of California, 1997, 184p.
- V.M.Verzhbitsky, "Computational linear algebra", Moscow, Higher School of Economics, 2009. 351 p.
- A.I.Zhdanov, "Introduction to methods for solving ill-posed problems", Samara, Aerospace University, 2006, –87 p.
- Ch.Lawson, R.Henson, "Numerical solution of problems in the method of least squares", 1986, 232 p.
- Yusupbekov, N.R., Igamberdiev, H.Z., Mamirov, U.F.: Adaptive Control System with a Multilayer Neural Network under Parametric Uncertainty Condition. In: Russian Advances in Fuzzy Systems and Soft Computing: selected contributions to the 8-th International Conference on Fuzzy Systems, Soft Computing and Intelligent Technologies (FSSCIT-2020), Vol. 2782, pp. 228-234. CEUR Workshop Proceedings, Aachen, Germany. doi: http://ceur-ws.org/Vol-2782/paper_32.pdf.