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An efficient decentralized robust adaptive controller for a class of large-scale non-affine nonlinear systems with strong interactions

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Abstract

This paper proposed a novel combination of decentralized robust adaptive radial basis neural network controller for a class of large-scale nonlinear non-affine systems with unknown subsystems and strong interconnections. Some suitable adaptive rules based on neural network are introduced that make all signals bounded, and also Lyapunov theory guaranteed tracking error signal asymptotically reaches zero. To show the effectiveness of the proposed method, some numerical results are presented. Furthermore, to evaluate the performance of the suggested method, a decentralized adaptive method is adopted from the literature and applied for comparison. Simulation results verify the desirable performance of the proposed controller.

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Authors and Affiliations

  1. Department of Electrical Engineering, Islamic Azad University, Najafabad Branch, Isfahan, Iran

    Morteza Ghateei

  2. Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran

    Ehsan Bijami

Authors
  1. Morteza Ghateei
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  2. Ehsan Bijami
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Correspondence to Ehsan Bijami.

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Ghateei, M., Bijami, E. An efficient decentralized robust adaptive controller for a class of large-scale non-affine nonlinear systems with strong interactions. Neural Comput & Applic 24, 463–471 (2014). https://doi.org/10.1007/s00521-012-1246-1

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  • DOI: https://doi.org/10.1007/s00521-012-1246-1

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