Adaptive observers for nonlinear systems based on dynamic extension and mixing procedure
https://doi.org/10.17586/0021-3454-2023-66-10-828-833
Abstract
The problem of synthesizing an adaptive observer of state variables of nonlinear dynamic systems is considered. Correct estimation of state vector components under parametric uncertainty is a rather complex process necessary e.g. for solving several problems of systems control and diagnostic. Synthesis of the proposed adaptive observer consists of two steps. In the first one, a parameterization of the nonlinear dynamical system, which can be transformed to a state affine form, is performed. In the second step, the unknown parameters are estimated based on the gradient descent method, and a gradient-based observer for the state variables is designed.
Keywords
adaptive observer,
nonlinear system parameterization,
affine state form,
global convergence,
parameter estimation
Supporting agencies: The work was carried out with the support of the Ministry of Science and Higher Education of the Russian Federation, state assignment passport 2019-0898.
About the Authors
V. V. Bespalov
ITMO University
Russian Federation
Russian Federation
Vladimir V. Bespalov - Faculty of Control Systems and Robotics
St. Petersburg
А. А. Vedyakov
ITMO University
Russian Federation
Russian Federation
Alexey А. Vedyakov - PhD, Faculty of Control Systems and Robotics
St. Petersburg
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For citations:
Bespalov V.V., Vedyakov А.А. Adaptive observers for nonlinear systems based on dynamic extension and mixing procedure. Journal of Instrument Engineering. 2023;66(10):828-833. (In Russ.) https://doi.org/10.17586/0021-3454-2023-66-10-828-833
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