Optimal Control System Synthesis Based on the Approximation of Extremals by Symbolic Regression

The article presents a solution to the optimal control synthesis problem based on the approximation of extremals. At the first stage it is proposed to solve the optimal control problem for various initial states, and at the second stage, to use the found optimal trajectories to determine the structure of the synthesizing function. Symbolic regression methods are used for approximation. Simulation is carried out for a car-like robot. The structure of the synthesizing function is found by the network operator method. A comparison of the solutions obtained using the synthesizing function found for the set of initial conditions with known solutions allows concluding that the proposed method is effective for the optimal control system synthesis. © 2020 EUCA.

Authors
Konstantinov S.V. 1 , Diveev A.I. 2 , Sofronova E.A. 2 , Zelinka I.3
Publisher
Institute of Electrical and Electronics Engineers Inc.
Language
English
Pages
2021-2026
Status
Published
Number
9143798
Year
2020
Organizations
  • 1 Academy of Sciences and RUDN University, Federal Research Center 'Computer Science and Control' of Russian, Moscow, Russian Federation
  • 2 Academy of Sciences, Federal Research Center 'Computer Science and Control' of Russian, Moscow, Russian Federation
  • 3 Faculty of Electrical Engineering and Computer Science VŠB-TUO, Department of Computer Science, Ostrava-Poruba, Czech Republic
Keywords
Optimal control systems; Regression analysis; Car-like robot; Initial conditions; Initial state; Network operator; Optimal control problem; Optimal controls; Optimal trajectories; Symbolic regression; Control system synthesis
Date of creation
02.11.2020
Date of change
02.11.2020
Short link
https://repository.rudn.ru/en/records/article/record/64796/