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A New Combination Method for Fuzzy Optimal Control

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Progress in Intelligent Decision Science (IDS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1301))

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Abstract

In this paper, we present a new hybrid method for solving fuzzy optimal control problems (FOCP). This hybrid method consists of a polynomial and an improved multi-layer perceptron (IMLP) network neural network. An improved neural network is a two-layer neural network. The first layer consists of inputs, weights, and six non-linear sigmoid transfer functions per α-cut and every training point. The second layer, which is the same output layer, includes the weights of the output layer and the neural network outputs, and six linear transfer functions per α-cut and each educational point. Artificial Neural Network training is based on the optimization technique on the target function. This objective function is the error function, and is equal to the sum of the squared errors that are based on the Pontryagin minimization principle.

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Author information

Authors and Affiliations

  1. Department of Applied Mathematics, Hamedan Branch, Islamic Azad University, 65138, Hamedan, Iran

    Sahar Askari

  2. Department of Mathematics, Faculty of Science, Imam Khomeini International University, 34194-288, Qazvin, Iran

    Saeid Abbasbandy

Authors
  1. Sahar Askari
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  2. Saeid Abbasbandy
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Corresponding author

Correspondence to Saeid Abbasbandy .

Editor information

Editors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Tofigh Allahviranloo

  2. Faculty of Engineering and Natural Sciences, Bahçeşehir University, Istanbul, Turkey

    Soheil Salahshour

  3. Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey

    Nafiz Arica

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Askari, S., Abbasbandy, S. (2021). A New Combination Method for Fuzzy Optimal Control. In: Allahviranloo, T., Salahshour, S., Arica, N. (eds) Progress in Intelligent Decision Science. IDS 2020. Advances in Intelligent Systems and Computing, vol 1301. Springer, Cham. https://doi.org/10.1007/978-3-030-66501-2_10

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