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Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2023-23-4-850-853
Adaptive observer for state variables of a time-varying nonlinear system with unknown constant parameters and delayed measurements
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Article in Russian
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Abstract
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Bobtsov A.A., Nikolaev N.A., Kozachek O.A., Oskina O.V. Adaptive observer for state variables of a time-varying nonlinear system with unknown constant parameters and delayed measurements. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2023, vol. 23, no. 4, pp. 850–853 (in Russian). doi: 10.17586/2226-1494-2023-23-4-850-853
Abstract
Unknown constant parameters estimation problem for a nonlinear time-varying system with delayed measurements is considered. The objective of this work is to design an adaptive observer for a nonlinear time-varying system. The observer must provide asymptotic convergence of the unknown constant parameters estimates to their true values. The main idea behind the method is to perform the parametrization of initial dynamical system based on GPEBO (Generalized Parameter Estimation Based Observer) technology and to build a linear regression model. The identification of linear regression model unknown parameters is performed using least square method with forgetting factor. This work develops the previously published approach for the case of nonlinear time-varying systems with delayed measurements. New parameters estimation algorithm can be applied for technical tasks, such as technical condition control and automatic control systems design.
Keywords: parameters identification, linear regression, delay
Acknowledgements. This work was supported by Russian Science Foundation, project no. 22-21-00499, https://rscf.ru/project/22-21-00499.
References
Acknowledgements. This work was supported by Russian Science Foundation, project no. 22-21-00499, https://rscf.ru/project/22-21-00499.
References
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