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Approximating the Solution of Optimal Control Problems by Fuzzy Systems

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Abstract

In this paper, the ability of fuzzy systems is used to estimate the solution of crisp optimal control problems. To solve an optimal control problem, first the well-known Euler–Lagrange conditions are obtained and then, the solution of these conditions is approximated by defining a trial solution based on fuzzy systems. The parameters of fuzzy systems are adjusted by an optimization algorithm. Numerical examples and comparisons with exact solutions reveal the capability and accuracy of proposed method.

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Acknowledgments

The authors are thankful to the unknown referees for their valuable and informative comments that have significantly improved the quality of the paper. They also appreciate the Editors and Editor in Chief for their valuable suggestions.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran

    Morteza Pakdaman & Sohrab Effati

  2. Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran

    Morteza Pakdaman & Sohrab Effati

Authors
  1. Morteza Pakdaman
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  2. Sohrab Effati
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Correspondence to Morteza Pakdaman.

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Pakdaman, M., Effati, S. Approximating the Solution of Optimal Control Problems by Fuzzy Systems. Neural Process Lett 43, 667–686 (2016). https://doi.org/10.1007/s11063-015-9440-7

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  • DOI: https://doi.org/10.1007/s11063-015-9440-7

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