EVOLUTIONARY ALGORITHMS FOR THE PROBLEM OF OPTIMAL CONTROL

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Abstract


The paper describes some of the popular evolutionary algorithms: genetic algorithms, differential evolution method, particle swarm optimization and bat-inspired method. With the help of these algorithms the problem of optimal control of a mobile robot is solved. For comparison the same problem is solved with the algorithm of fast gradient descent and random search. The computational experiments showed that evolutionary algorithms provide more accurate results for the optimal control problems than fast gradient descent algorithm.


A I Diveev

Principal contact for editorial correspondence.
aidiveev@mail.ru
Institution of Russian Academy of Sciences Dorodnicyn Computing Centre of RAS; Peoples’ Friendship University of Russia (RUDN University) Vavilova str., 40, Moscow, Russia, 119333; Miklukho-Maklaya str., 6, Moscow, Russia, 117198

Doctor of technical sciences, professor, chief of sector of Cybernetic problems, Federal Research Centre “Computer Science and Control” of Russia Academy of Sciences, professor of department Mechanics and mechatronics, Engineering Academy, Peoples’ Friendship University of Russia (RUDN University)

S V Konstantinov

konstantinov_sv@rudn.university
Peoples’ Friendship University of Russia (RUDN University) Miklukho-Maklaya str., 6, Moscow, Russia, 117198

senior lecturer of department Mechanics and mechatronics, Engineering Academy, Peoples’ Friendship University of Russia (RUDN University). Research interests: Optimization algorithms, evolutionary algorithms, genetic algorithms, computational methods for problems of optimal control

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