Abstract
A problem of synthesized control for mobile robot is considered. Initially, a control synthesis problem is solved and a function is found that ensures the stability of the object relative to a point in the state space. The coordinates of the stability points are searched so that when switching form point to point over a given time interval, the robot moves from the initial conditions to the terminal ones without collisions and with the optimal value of the quality criterion. To solve a control synthesis problem a method of complete binary genetic programming is used. To find the coordinates of stability points a particle swarm optimization is applied. Experiments for object with uncertainties in the right parts are given. The sensitivity to different levels of noise for obtaining optimal control by three methods are presented.
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References
Koza, J.R.: Human-competitive results produced by genetic programming. Genet. Program Evolvable Mach. 11, 251–284 (2010)
Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., Lillicrap, T., Simonyan, K., Hassabis, D.: A general reinforcement learning algorithm that masters chess, shogi, and go through self-play. Science 362(6419), 1140–1144 (2018). https://doi.org/10.1126/science.aar6404
Diveev, A.I., Kazaryan, D.E., Sofronova, E.A.: Symbolic regression methods for control system synthesis. In: Proceedings of the 22nd Mediterranean Conference on Control and Automation (MED), 16–19 June 2014, pp. 587–592. University of Palermo, Palermo, Italy (2014)
Dang, T.P., Diveev, A.I. Sofronova, E.A.: A problem of identification control synthesis for mobile robot by the network operator method. In: Proceedings of the 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016), Hefei, China, 5–7 June 2016, pp. 2413–2418 (2016)
Diveev, A., Sofronova, E., Ryndin, D.: Control synthesis by network operator method for spacecraft descent on the Moon. Adv. Astronaut. Sci. 161, 873–883 (2017)
Zelinka, I., Nolle, L., Oplatkova, Z.: Analytic programming - symbolic regression by means of arbitrary evolutionary algorithms. J. Simul. 6(9), 44–56 (2005)
Diveev, A., Balandina, G., Konstantinov, S.: Binary variational genetic programming for the problem of synthesis of control system. In: Proceedings of the 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2017), Guilin, China, 29–31 July 2017, pp. 165–170 (2017)
Poli, R., Langdon, W.B., McPhee, N.F.: A Field Guide to Genetic Programming, 233 p. (2008). ISBN 978-1-4092-0073-4
Pontryagin, L.S., Boltyanskii, V.G., Gamkrelidze, R.V., Mishchenko, E.F.: The Mathematical Theory of Optimal Process, vol. 4 in Pontryagin, L. S. Gordon and Breach Science Publishers, New York, 360 p. (1985). Selected Works
Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, Perth, Australia, IV, pp. 1942–1948 (1995)
Diveev, A.I., Konstantinov, S.V.: Study of the practical convergence of evolutionary algorithms for the optimal program control of a wheeled robot. J. Comput. Syst. Sci. Int. 57(4), 561–580 (2018)
Arutyunov, A.V., Karamzin, D.Y.: Non-degenerate necessary optimality conditions for the optimal control problem with equality-type state constraints. J. Global Optim. 64(4), 623–647 (2016)
Arutyunov, A.V., Karamzin, D.Y., Pereira, F.L.: Maximum principle in problems with mixed constraints under weak assumptions of regularity. Optimization 59(7), 1067–1083 (2010)
Acknowledgments
This research was partially supported by Russian Foundation for Basic Research, project 18-29-03061-mk.
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Diveev, A., Sofronova, E. (2020). Automation of Synthesized Optimal Control Problem Solution for Mobile Robot by Genetic Programming. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_77
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DOI: https://doi.org/10.1007/978-3-030-29513-4_77
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