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Adaptive Decentralized Tracking Control for a Class of Large-Scale Nonlinear Systems with Dynamic Uncertainties Using Multi-dimensional Taylor Network Approach

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Abstract

For the large-scale nonlinear systems subject to dynamic uncertainties, an adaptive multi-dimensional Taylor network (MTN)-based decentralized control strategy is proposed, which can effectively solve output tracking control problem of the systems. Firstly, a dynamic signal is introduced to cope with the problem of unknown nonlinear dynamic uncertainties. Secondly, in each step of the backstepping, only one MTN is used to approximate the combination of unknown nonlinear functions. Then, in the last step of the backstepping, a new adaptive control scheme is designed, which realizes the stability and boundedness of the controlled systems. It is worth noting that the large-scale nonlinear systems, the unknown dynamic uncertainties and the MTN appear in the same framework for the first time. Finally, three simulation examples are presented to verify the feasibility of the proposed control strategy.

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Funding

Funding was provided by Natural Science Foundation of Shandong Province (Grant No. ZR2020QF055).

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Authors and Affiliations

  1. School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao, 266061, China

    Zheng-Duo Shan, Wen-Jing He, Yu-Qun Han & Shan-Liang Zhu

  2. The Research Institute for Mathematics and Interdisciplinary Sciences, Qingdao University of Science and Technology, Qingdao, 266061, China

    Yu-Qun Han & Shan-Liang Zhu

Authors
  1. Zheng-Duo Shan
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  2. Wen-Jing He
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  3. Yu-Qun Han
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  4. Shan-Liang Zhu
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Correspondence to Shan-Liang Zhu.

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Shan, ZD., He, WJ., Han, YQ. et al. Adaptive Decentralized Tracking Control for a Class of Large-Scale Nonlinear Systems with Dynamic Uncertainties Using Multi-dimensional Taylor Network Approach. Neural Process Lett 55, 3509–3531 (2023). https://doi.org/10.1007/s11063-022-11020-3

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