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In this paper, we propose a multiple-order time-delay Zhang neural dynamics (MOTDZND) model for handling the tracking control problem of the chaotic system with mixed input. The key technique of the MOTDZNN model is to approximate multiple-order derivatives of the desired path by using the backward finite difference (BFD) rules. By adopting a group of BFD rules, we develop a MOTDZND model, whose truncation error is square-form, for handling the tracking control problem of the chaotic system with mixed input. A group of simulations verifies that the proposed model is validity and consist with the theoretical square-form truncation error.

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Multiple-order Time-Delay Zhang Neural Dynamics Model for Handling Tracking Control Problem of Lu Chaotic System with Mixed Inputs

  • 会议论文

  • 发表日期：

    2026年

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  • Pengfei Guo,
  • Yunong Zhang

摘要

In this paper, we propose a multiple-order time-delay Zhang neural dynamics (MOTDZND) model for handling the tracking control problem of the chaotic system with mixed input. The key technique of the MOTDZNN model is to approximate multiple-order derivatives of the desired path by using the backward finite difference (BFD) rules. By adopting a group of BFD rules, we develop a MOTDZND model, whose truncation error is square-form, for handling the tracking control problem of the chaotic system with mixed input. A group of simulations verifies that the proposed model is validity and consist with the theoretical square-form truncation error.