doi: 10.17586/2226-1494-2024-24-4-554-562


Synthesis of adaptive observer for nonlinear nonstationary systems

K. Nguyen, S. M. Vlasov, A. A. Pyrkin, K. Y. Kalinin, M. Nguyen, V. Nguyen, V. Bui


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Nguyen K.T., Vlasov S.M., Pyrkin A.A., Kalinin K.Yu., Nguyen M.H., Nguyen V.V., Bui V.H. Synthesis of adaptive observer for nonlinear nonstationary systems. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2024, vol. 24, no. 4, pp. 554–562 (in Russian). doi: 10.17586/2226-1494-2024-24-4-554-562 


Abstract
A new method for the synthesis of adaptive state observation for a class of nonlinear non-stationary systems is proposed. This task is important and fundamental in control theory and is related to both the control problem and the task of monitoring the efficiency of the system operation. The solution to the problem is based on the generalized observer parameter estimation method to obtain the regression equation necessary for estimating the state and parameters of the system. Further, the dynamic regressor expansion and blending method dynamic regressor extension and mixing method is applied to identify the unknown system parameters. The paper proposes a method for estimating the state vector for a nonlinear non-stationary system in which the unknown parameters depend on the state vector under external disturbances. The results obtained are rigorously proved using mathematical theory. Simulation in Matlab/Simulink is performed to demonstrate the effectiveness of the developed algorithm. The mathematical model of the considered objects is a nonlinear system of equations with variable parameters. Compared to previous methods, the method proposed in this paper is more general, especially in a system where the unknown parameters depend on the state vector with nonlinear functions. However, the problem is currently solved only for discrete systems. In the future, it may be possible to extend it to continuous systems.

Keywords: adaptive control, synthesis of adaptive observer, identification, nonlinear nonstationary system

Acknowledgements. The work was supported by the Ministry of Science and Higher Education of the Russian Federation, Agreement No. 2019-0898.

References
  1. Bobtsov A.A., Nagovitsina A.G. Adaptive control of linear nonstationary objects output. Automation and Remote Control, 2006, vol. 67, no. 12, pp. 2010–2020. https://doi.org/10.1134/S0005117906120137
  2. Bobtsov A.A., Grigoryev V.V., Nagovitsina A.G. Adaptive control algorithm by nonstationary object in terms of disturbance and delay time. Mekhatronika, Avtomatizatsiya, Upravlenie, 2007, no. 1, pp. 8–14. (in Russian)
  3. Dung Kh.B., Pyrkin A.A., Bobtsov А.А., Vedyakov А.А. Identification of polynomial parameters of nonstationary linear systems. Journal of Instrument Engineering, 2021, vol. 64, no. 6, pp. 459–468. (in Russian). https://doi.org/10.17586/0021-3454-2021-64-6-459-468
  4. Le V.T., Korotina M.M., Bobtsov A.A., Aranovskiy S.V., Vo Q.D. Identification of linear time-varying parameters of nonstationary systems. Mekhatronika, Avtomatizatsiya, Upravlenie, 2019, vol. 20, no. 5, pp. 259–265. (in Russian). https://doi.org/10.17587/mau.20.259-265
  5. Wang J., Le Vang T., Pyrkin A.A., Kolyubin S.A., Bobtsov A.A. Identification of piecewise linear parameters of regression models of non-stationary deterministic systems. Automation and Remote Control, 2018, vol. 79, no. 12, pp. 2159–2168. https://doi.org/10.1134/s0005117918120068
  6. Dang Binh Khac, Pyrkin A.A., Bobtsov A.A., Vedyakov A.A. Adaptive observer design for time-varying nonlinear systems with unknown polynomial parameters. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2021, vol. 21, no. 3, pp. 374–379. (in Russian). https://doi.org/10.17586/2226-1494-2021-21-3-374-379
  7. Bobtsov A.A., Nikolaev N.A., Ortega Martinez R., Slita O.V., Kozachek O.A. Adaptive state observer for linear time-varying system with partially unknown state matrix and input matrix parameters.  Mekhatronika, Avtomatizatsiya, Upravlenie, 2022, vol. 23, no. 6, pp. 283–288. (in Russian). https://doi.org/10.17587/mau.23.283-288
  8. Bobtsov A.A., Lyamin A.V., Sergeev K.A. Synthesis of the law of adaptive control for stabilization of not exactly specified non-stationary objects. Journal of Instrument Engineering, 2001, no. 3, pp. 3–7. (in Russian)
  9. Quoc D.V., Bobtsov A.A. An adaptive state observer for linear time-varying systems with inaccurate parameters. Automation and Remote Control, 2020, vol. 81, no. 12, pp. 2220–2229. https://doi.org/10.1134/S0005117920120061
  10. Tsykunov A.M. Robust control of nonstationary plants. Automation and Remote Control, 1996, vol. 57, no. 2, pp. 248–255.
  11. Kleiman E.G., Mochalov I.A. Identification of time-dependent plants. Automation and Remote Control, 1994, vol. 55, no. 2, pp. 149–163.
  12. Pyrkin A., Bobtsov A., Ortega R., Vedyakov A., Aranovskiy S. Adaptive state observers using dynamic regressor extension and mixing. Systems & Control Letters, 2019, vol. 133, pp. 104519. https://doi.org/10.1016/j.sysconle.2019.104519
  13. Ortega R., Bobtsov A., Nikolaev N., Schiffer J., Dochain D. Generalized parameter estimation-based observers: Application to power systems and chemical–biological reactors. Automatica, 2021, vol. 129, pp. 109635. https://doi.org/10.1016/j.automatica.2021.109635
  14. Aranovskiy S., Bobsov A., Ortega R., Pyrkin A. Performance enhancement of parameter estimators via dynamic regressor extension and mixing. IEEE Transactions on Automatic Control, 2017, vol. 62, no. 7, pp. 3546–3550. https://doi.org/10.1109/tac.2016.2614889


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