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Tracking problem of non-particle morphology based on fixed-time ZNN model

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  • Miao, Peng
  • Li, Shuai
  • Li, Chenghang

Abstract

This article examines a particular tracking challenge where targets and trackers cannot be conceptualized as static points and are continuously rotating. This poses difficulties in determining the shortest distance between them. To rapidly and precisely ascertain this minimal distance, we formulate an optimization problem. Subsequently, a fixed-time zeroing neural network (ZNN) model is devised to address this optimization challenge. Moreover, the fixed-time stability of the proposed network is established and an estimation of a relatively smaller upper bound of convergence time (UBCT) is derived from previous iterations. Furthermore, the sensitivity of parameters to UBCT is also given. Finally, a specific tracking scenario demonstrates the efficacy and superior performance of our approach.

Suggested Citation

  • Miao, Peng & Li, Shuai & Li, Chenghang, 2025. "Tracking problem of non-particle morphology based on fixed-time ZNN model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 238(C), pages 189-200.
    • Handle: RePEc:eee:matcom:v:238:y:2025:i:c:p:189-200
    DOI: 10.1016/j.matcom.2025.04.039
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    References listed on IDEAS

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    1. Xiao, Lin & Li, Linju & Cao, Penglin & He, Yongjun, 2023. "A fixed-time robust controller based on zeroing neural network for generalized projective synchronization of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    2. Miao, Peng & Zheng, Yuhua & Li, Shuai, 2024. "A new FXTZNN model for solving TVCS equation and application to pseudo-inverse of a matrix," Applied Mathematics and Computation, Elsevier, vol. 465(C).
    3. Peng Tang & Jiyun Li & Hongqiang Sun, 2024. "A Review of Electric UAV Visual Detection and Navigation Technologies for Emergency Rescue Missions," Sustainability, MDPI, vol. 16(5), pages 1-22, March.
    Full references (including those not matched with items on IDEAS)

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