Pseudospectral Method for Finding Optimal Control of Trajectory Bundles Based on Multi-Agent Optimization Algorithms

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Abstract

A class of problems of optimal control of nonlinear continuous deterministic systems under conditions of uncertainty is considered. To solve the problem, a numerical algorithm for finding the optimal control is formed, in which the parameterization of the control law is used, which depends on time and a set of coordinates of the state vector available for measurement. This approach is based on the approximation of the control law by a series using a system of basis functions with unknown coefficients. The search for unknown coefficients in the expansion of the control law is implemented using multi-agent optimization methods: a hybrid multi-agent interpolation search algorithm and a multi-agent algorithm based on the use of linear controllers for controlling the movement of agents. A software has been developed and two model examples and an applied problem of stabilizing a satellite with the help of engines installed on it have been solved.

General Information

Keywords: optimal control, multi-agent optimization algorithms, trajectory bundle, Chebyshev polynomials, pseudospectral method

Journal rubric: Optimization Methods

Article type: scientific article

DOI: https://doi.org/10.17759/mda.2023130206

Received: 17.03.2023

Accepted:

For citation: Karane M.S. Pseudospectral Method for Finding Optimal Control of Trajectory Bundles Based on Multi-Agent Optimization Algorithms. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2023. Vol. 13, no. 2, pp. 99–122. DOI: 10.17759/mda.2023130206. (In Russ., аbstr. in Engl.)

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Information About the Authors

Mary Magdalene S. Karane, Postgraduate Student of the Institute "Computer Science and Applied Mathematics", Moscow Aviation Institute (National Research University), Moscow, Russia, ORCID: https://orcid.org/0000-0002-8019-8613, e-mail: mmarselina@mail.ru

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