Approximate Method for Synthesizing Continuous Joint Estimation and Control Systems Via the State-Dependent Riccati Equation Technique

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Abstract

The problem of approximate synthesis of a closed loop nonlinear continuous system of joint estimation and control is considered. An approach is used based on the application of the idea of the separation theorem for linear dynamical systems. Using the factorization operation, a nonlinear system is transformed into a structure similar to a linear system, and algorithms for synthesizing an optimal linear controller and state observer are applied to the transformed system, a feature of which is the dependence of the matrices included in the corresponding Riccati equations on the state vector. An example of the synthesis of a state observer and a controller is given, demonstrating the application of the proposed algorithm.

General Information

Keywords: optimal linear controller, state observer, separation principle, state-dependent Riccati equation, nonlinear dynamical system

Journal rubric: Optimization Methods

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2024140303

Received: 25.05.2024

Accepted:

For citation: Panteleev A.V., Khvoshnyanskaya E.A. Approximate Method for Synthesizing Continuous Joint Estimation and Control Systems Via the State-Dependent Riccati Equation Technique. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2024. Vol. 14, no. 3, pp. 41–62. DOI: 10.17759/mda.2024140303. (In Russ., аbstr. in Engl.)

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Information About the Authors

Andrey V. Panteleev, Doctor of Physics and Matematics, Professor, Head of the Department of Mathematical Cybernetics, Institute of Information Technologies and Applied Mathematics, Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0000-0003-2493-3617, e-mail: avpanteleev@inbox.ru

Elizaveta A. Khvoshnyanskaya, Master’s Degree Student of the Institute “Computer Science and Applied Mathematics”, Moscow Aviation Institute (National Research University) (MAI), Moscow, Russia, ORCID: https://orcid.org/0009-0009-6901-8720, e-mail: liza190401@mail.ru

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