Другие журналы
scientific edition of Bauman MSTU
SCIENCE & EDUCATION
Bauman Moscow State Technical University. El № FS 77 - 48211. ISSN 1994-0408
The Comparison of Methods for Genetic and Variational Genetic Programming Using a Control Synthesis Problem for the Model "Predator-Victim" as an Example
# 05, May 2014
DOI: 10.7463/0514.0709252
Article file:
Diveev_A.pdf
(901.87Kb)
Diveev_A.pdf
(901.87Kb)
This paper studies numerical methods to solve the problem of control system synthesis.
Two symbolical regression methods are compared such as a genetic programming method and a new variational genetic programming method. First, the paper provides the qualitative comparative analysis of methods and gives the numerical estimations of resources to be used by the methods. Then the methods are applied to solve a control system synthesis problem. The non-linear model of the "predator-prey" system is considered. To obtain the reliable results an identical values were assigned to the initial parameters of the search algorithms for both methods. A trivial basic solution is chosen for the variational genetic programming method, though the main advantage of this method is the possibility to reduce time of calculations owing to experienced developer's choice of the basic solution that is close to an optimal one.
We performed a computational experiment to show that the variational genetic programming method finds a many times faster solution and spends less resources, and a received result provides better values of the goal functions, than the genetic programming method. In the future it is necessary to compare these methods using a complex challenging control system synthesis problem where it can be proven that the method of variational genetic programming has an advantage arising from the choice of the specific basic solution. It is also necessary to compare the method of variational genetic programming with other symbolic regression methods, such as analytical programming, grammatical evolution and network operator methods.
References
- Diveev A.I., Sofronova E.A. Metod setevogo operatora i ego primenenie v zadachakh upravleniya [Method of network operator and its application in problems of control]. Moscow, Peoples’ Friendship University of Russia Publ., 2012. 182 p. (in Russian).
- Diveev A.I. [A numerical method for network operator for synthesis of a control system with uncertain initial values]. Izvestiya RAN. Teoriya i sistemy upravleniya , 2012, no. 2, pp. 63-78. ( English translation: Journal of Computer and Systems Sciences International, 2012, vol. 51, iss. 2, pp. 228-243. DOI: 10.1134/S1064230712010066 ).
- Diveev A.I., Kazaryan D.E. [Grammatical evolution and network operator methods for synthesis of the control system for a dynamic object]. Sovremennye problemy nauki i obrazovaniya - Modern problems of science and education , 2013, no. 4. Available at: http://www.science-education.ru/110-9546, accessed 01.04.2014. (in Russian).
- Rogachev G.N., Egorov V.A. [ Genetic programming in search problems of systems engineering solutions ]. 7-y Mezhdunarodnyy simpozium “Intellektual'nye sistemy” (INTELS’2006): tr. [Proc. of the 7th International Symposium “Intelligent Systems” (INTELS'2006) ]. Krasnodar, 26-30 June 2006. Moscow, RUSAKI Publ., 2006, pp. 69-72. (in Russian).
- Rogachev G.N. [ Genetic programming in search problems of systems engineering solutions ]. Vestnik Samarskogo gosudarstvennogo tekhnicheskogo universiteta. Ser. Tekhnicheskie nauki , 2006, no. 40, pp. 37-42. (in Russian).
- Ibadulla S.I., Diveev A.I., Sofronova E.A. [Control system problem solution by variational genetic programming method]. Sovremennye problemy nauki i obrazovaniya - Modern problems of science and education, 2013, no. 6. Available at: http://www.science-education.ru/113-11697, accessed 01.04.2014. (in Russian).
- Bourmistrova A., Khantsis S. Control System Design Optimization via Genetic Programming. Proceedings of CEC 2007. IEEE Congress on Evolutionary Computation , 2007, pp. 1993-2000. DOI: 10.1109/CEC.2007.4424718
- Koza J.R. Genetic Programming: On the Programming of Computers by Means of Natural Selection . Cambridge, Massachusetts, London, MA, MIT Press. 1992. 819 p.
- Koza J.R., Keane M.A., Streeter M.J., Mydlowec W., Yu J., Lanza G. Genetic Programming IV. Routine Human-Competitive Machine Intelligence . Springer US, 2003. 606 p. DOI: 10.1007/b137549
- Sager S. A Benchmark Library of Mixed-Integer Optimal Control Problems. In: Lee J., Leyffer S. , eds. Mixed Integer Nonlinear Programming . Springer New York, 2012, pp. 631-670. DOI: 10.1007/978-1-4614-1927-3_22
Publications with keywords: synthesis of control system, the method of variations of the basis solutions, variational genetic programming
Publications with words: synthesis of control system, the method of variations of the basis solutions, variational genetic programming
See also:
Thematic rubrics:
Поделиться:
| Authors |
| Press-releases |
| Library |
| Conferences |
| About Project |
| Phone: +7 (915) 336-07-65 (строго: среда; пятница c 11-00 до 17-00) |
|
 |
|||
| © 2003-2024 «Наука и образование» Перепечатка материалов журнала без согласования с редакцией запрещена Phone: +7 (915) 336-07-65 (строго: среда; пятница c 11-00 до 17-00) | |||||
