Abstract
Determination of the suboptimal programmed control for the continuous deterministic systems by the use of the method of artificial immune systems for search of the conditional global extremum was proposed. An algorithm to solve it which underlies the corresponding software was generated, and a modification of the method was suggested to enhance its efficiency. Examples of solutions of the model problems were given, and the method of artificial immune systems was compared with its modification, as well as with other metaheuristic methods.
Similar content being viewed by others
References
de Castro, L.N. and von Zuben, F.J., Learning and Optimization Using the Clonal Selection Principle, IEEE Trans. Evol. Comput., 2002, vol. 6, no. 3, pp. 239–251.
de Castro, L. and Timmis, J., An Artificial Immune Network for Multimodal Function Optimization, in Proc. IEEE Congr. Evol. Comput., 2002, vol. 1, pp. 669–674.
de Castro, L.N., von Zuben, F.J., and Knidel, H., Artificial Immune Systems, in Proc. 7 Int. Conf. ICARIS, Heidelberg, 2007, vol. 4628.
Dasgupta, D., Artificial Immune Systems and Their Applications, Berlin: Springer, 1999. Translated under the title Iskusstvennye immunye sistemy i ikh primenenie, Moscow: Fizmatlit, 2006.
Metlitskaya, D.V., Algorithmic Support of the Modified Method of Artificial Immune Systems, in Teoreticheskie voprosy vychislitel’noi tekhniki i programmnogo obespecheniya. Mezhvuz. sb. nauchn. tr. MIREA (Theoretical Issues of Computer Engineering and Software. MIREA Collected Papers), 2011, pp. 81–86.
Panteleev, A.V. and Bortakovskii, A.S., Teoriya upravleniya v primerakh i zadachakh (Control Theory in Examples and Problems), Moscow: Vysshaya Shkola, 2003.
Panteleev, A.V., Metaevristicheskie algoritmy poiska global’nogo extremuma (Metaheuristic Algorithms to Seek Global Extremum), Moscow: MAI-PRINT, 2009.
Kireev, V.I. and Panteleev, A.V., Chislennye metody v primerakh i zadachakh (Numerical Methods in Examples and Problems), Moscow: Vysshaya Shkola, 2008.
Panteleev, A.V. and Metlitskaya, D.V., Formation of the Genetic Algorithms with Real Coding in the Problem of Design of Optimal Control of D Systems, Aviakosm. Priborostr., 2011, no. 3, pp. 26–31.
Panteleev, A.V. and Metlitskaya, D.V., Application of the Genetic Algorithms with Real Coding to the Problem of Optimal Control of Discrete Systems, Vestn. Comput. Inf. Technol., 2011, no. 9, pp. 17–23.
Panteleev, A.V. and Metlitskaya, D.V., An Application of Genetic Algorithms with Binary and Real Coding for Approximate Synthesis of Suboptimal Control in Deterministic Systems, Autom. Remote Control, 2011, vol. 72, no. 11, pp. 2328–2338.
Panteleev, A.V. and Metlitskaya, D.V., Application of the Genetic Algorithms with Binary Coding to the Problem of Seeking the Optimal Control of Continuous Deterministic Systems, Aviakosm. Priborostr., 2011, no. 2, pp. 23–30.
Zubanov, N.V., Analiz ustoichivosti otnositel’no postavlennoi tseli kak odin iz podkhodov k opisaniyu funktsionirovaniya organizatsii v usloviyakh neopredelennosti (Analysis of Stability to the Posed Purpose as an Approach to Describing Operation of an Organization under Uncertainty), Samara: Samar. Gos. Tekhn. Univ., 2001.
Farhad Nadi, A Parameter-Less Genetic Algorithm with Customized Crossover and Mutation Operators, in Proc. 13 Conf. GECCO, Dublin, 2011, pp. 901–908.
Lopez Cruz, I.L., van Willigenburg, L.G., and van Straten, G., Evolutionary Algorithms for Optimal Control of Chemical Processes, in Wageningen Univ. Res. Publicat., Netherlands, 2000, pp. 155–161.
Luus, R., Iterative Dynamic Programming, New York: Chapman&Hall/CRC, 2000.
Author information
Authors and Affiliations
Corresponding author
Additional information
Original Russian Text © A.V. Panteleev, D.V. Metlitskaya, 2014, published in Avtomatika i Telemekhanika, 2014, No. 11, pp. 38–54.
Rights and permissions
About this article
Cite this article
Panteleev, A.V., Metlitskaya, D.V. Using the method of artificial immune systems to seek the suboptimal program control of deterministic systems. Autom Remote Control 75, 1922–1935 (2014). https://doi.org/10.1134/S0005117914110034
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S0005117914110034