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Dynamic programming strategy based on a type-2 fuzzy wavelet neural network

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Abstract

In this paper, an optimal control scheme, based on dynamic programming strategy, is presented for synchronization of uncertain fractional-order chaotic/hyperchaotic systems. In the scheme, a type-2 fuzzy wavelet neural network (T2FWNN) is proposed for estimation of the unknown functions in dynamics of system. For solving the fractional optimal control problem, fractional-order derivative is approximated by using Oustaloup recursive approximation method. Simulation studies verify the effectiveness of the proposed control scheme and the proposed T2FWNN.

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Acknowledgements

This paper is partly supported by the National Science Foundation of China (61473183, 61627810, U1509211).

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Bonab, Bonab, Iran

    Ardashir Mohammadzadeh

  2. Department of Automation, Shanghai Jiaotong University, Shanghai, 200240, People’s Republic of China

    Weidong Zhang

  3. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, 200444, People’s Republic of China

    Weidong Zhang

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  1. Ardashir Mohammadzadeh
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  2. Weidong Zhang
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Correspondence to Weidong Zhang.

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Mohammadzadeh, A., Zhang, W. Dynamic programming strategy based on a type-2 fuzzy wavelet neural network. Nonlinear Dyn 95, 1661–1672 (2019). https://doi.org/10.1007/s11071-018-4651-x

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