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A Multilayer Feed Forward Small-World Neural Network Controller and Its Application on Electrohydraulic Actuation System

Author

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  • Xiaohu Li
  • Feng Xu
  • Jinhua Zhang
  • Sunan Wang

Abstract

Being difficult to attain the precise mathematical models, traditional control methods such as proportional integral (PI) and proportional integral differentiation (PID) cannot meet the demands for real time and robustness when applied in some nonlinear systems. The neural network controller is a good replacement to overcome these shortcomings. However, the performance of neural network controller is directly determined by neural network model. In this paper, a new neural network model is constructed with a structure topology between the regular and random connection modes based on complex network, which simulates the brain neural network as far as possible, to design a better neural network controller. Then, a new controller is designed under small-world neural network model and is investigated in both linear and nonlinear systems control. The simulation results show that the new controller basing on small-world network model can improve the control precision by 30% in the case of system with random disturbance. Besides the good performance of the new controller in tracking square wave signals, which is demonstrated by the experiment results of direct drive electro-hydraulic actuation position control system, it works well on anti-interference performance.

Suggested Citation

  • Xiaohu Li & Feng Xu & Jinhua Zhang & Sunan Wang, 2013. "A Multilayer Feed Forward Small-World Neural Network Controller and Its Application on Electrohydraulic Actuation System," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-8, June.
  • Handle: RePEc:hin:jnljam:872790
    DOI: 10.1155/2013/872790
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    Cited by:

    1. Daewon Chung & Insoo Sohn, 2023. "Neural Network Optimization Based on Complex Network Theory: A Survey," Mathematics, MDPI, vol. 11(2), pages 1-12, January.
    2. Akhmet, Marat & Tleubergenova, Madina & Zhamanshin, Akylbek, 2024. "Cohen-Grossberg neural networks with unpredictable and Poisson stable dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    3. Erkaymaz, Okan & Ozer, Mahmut, 2016. "Impact of small-world network topology on the conventional artificial neural network for the diagnosis of diabetes," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 178-185.

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