Binary variational genetic programming for the problem of synthesis of control system

The paper describes a novel numerical symbolic regression method. It's called complete binary variational genetic programming. We use it for synthesis of optimal control. This method performs better than genetic programming at crossover, reduces the search area and speeds up search algorithm by using small variations. The efficiency of the new method is proven on the given example of control system synthesis for mobile robot. © 2017 IEEE.

Authors
Diveev A.I. 1 , Balandina G.I. 2 , Konstantinov S.V. 2
Conference proceedings
ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
Publisher
Institute of Electrical and Electronics Engineers Inc.
Language
English
Pages
186-191
Status
Published
DOI
10.1109/FSKD.2017.8393051
Year
2018
Organizations
  • 1 Federal Research Centre 'Computer Science and Control', Russian Academy of Sciences, Academy of Engineering, RUDN University, Moscow, Russian Federation
  • 2 Academy of Engineering, RUDN University, Moscow, Russian Federation
Keywords
genetic programming; optimal control; symbolic regression; synthesis of control
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