The problems of separate and generalized assessment of the state and parameters of controlled objects under conditions of varying degrees of a priori uncertainty are considered. Stable algorithms for the generalized estimation of the state and parameters based on the quasilinearization method and the formal model of motion under conditions of statistical uncertainty, as well as the correction of the results of the generalized estimation, are presented. It is shown that the considered regularized generalized coordinate and parametric estimation algorithms make it possible to recover with sufficient accuracy the extended state vector of a dynamical system. The above algorithms make it possible to stabilize the procedure for estimating the state of stochastic objects and thereby increase the accuracy of determining the true estimate of the state vector when the parameters of the object and observer are perturbed.
1. A.A.Krasovskiy, The directory under the theory of automatic control. Moscow: Science, 1987, 712 p.
2. K.T.Leondes, Filtration and stochastic control in dynamic systems. Trans. From English, Moscow: World, 1980, 407 p.
3. M.S.Yarlikov, Using Markov theories to nonlinear filtering in radio mechanic. Moscow: Radio, 1975.
4. Andrew P.Sage, James L.Melsa, System identification. Moscow: Science, 1974, 248 p.
5. P.Eykhoff, Bases to identifications managerial system. Moscow: World, 1975, 683 p.
6. V.Repin, G.Tarkovskiy, Statistical syntheses under a priori uncertainty and adapting the information systems. Moscow: Radio, 1997.
7. A.N.Tihonov, V.Y.Arsenin, Method of the decision of incorrect problems. Moscow: Science, 1979, 288 p.
8. V.A.Morozov, Regular methods of the decision it is incorrect tasks in view. Moscow: Science, 1987, 240 p.
9. N.Yusupbekov, H.Igamberdiev, U.Mamirov, “Algorithms Of Sustainable Estimation Of Unknown Input Signals In Control Systems”, Journal of Automation, Mobile Robotics & Intelligent System, vol. 12, no. 4, pp. 83-86, 2018.
10. H.Z.Igamberdiyev, A.N.Yusupbekov, O.O.Zaripov, J.U.Sevinov, “Algorithms of adaptive identification of uncertain operated objects in dynamical models”, Procedia computer science, vol. 120, pp. 854-861, 2017,
11. F.P.Vasiliev, The Methods to optimization. Publishers: Factorial Press, 2002, 824 p.
12. A.B.Bakushinskiy, A.V.Goncharskiy, Iterative methods of the decision of incorrect problems. Moscow: Science, 1989, 128 p.
13. G.M.Vaynikko, A.Yu.Veretennikov, Iteration procedures in incorrect exercises. Moscow: Science, 1986, 178 p.
14. P.D.Crutko, Inverse problems speakers operated systems. Moscow: Science, 1987, 304 p.
15. L.M.Homyakova, “To problem of the filtering in nonlinear managerial system”, Automation and telemechanics, no. 1, –pp. 65-71, 1979.
16. A.Y.Andrienko, “Method of estimations vector of the indignations to high dimensionality in problem of the forecasting of the final condition terminal managerial system”, Automation and telemechanics, no. 7, pp. 71-81, 1996.
17. H.Z.Igamberdiyev, U.F.Mamirov, “Sustainable estimation of parameters and covariation of disturbance vectors in uncertain systems”, Chemical Technology. Control and Management, no. 3, pp. 16-19, 2018.
18. B.F.Zhdanyuk, Bases of the statistical processing path measurements. Moscow: Radio, 1978.
19. I.V.Burlay, “Parametrical identification of the operated systems on the base of the extended model of the observations”, Notify Academies of the sciences. The theory and managerial system, no. 4, pp. 29 -34, 1997.
20. I.V.Burlay, “The regular methods of estimation condition object in dynamic and kinematicses to production”, Notify academies of the sciences. Theory and managerial system, no. 3, pp. 17-23, 2000.
Abdurakhmanova, Yulduz Muhtarhodjaeva
"Sustainable Algorithms For Generalized Estimation Of Dynamic Control Objects,"
Chemical Technology, Control and Management: Vol. 2019
, Article 7.
Available at: https://uzjournals.edu.uz/ijctcm/vol2019/iss5/7