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<p>This paper investigates the distributed tracking problem for second-order nonlinear time-varying multi-agent systems (SONTV-MASs) subject to unknown control directions (UCDs) and input dead-zone using adaptive iterative learning control (AILC). Through parameter recombination and mean value theorem, the system is remodeled. Based on these, time-varying gains are designed to avoid the global information related topology graph and distinctive multi-Nussbaum functions are introduced. Moreover, by constructing a weighted composite energy function (WCEF), it is strictly analyzed and proved that all followers completely track the leader in a finite time interval. Numerical simulations conducted on a multi-single-link manipulator system validate the theoretical results and demonstrate the algorithm’s effectiveness.</p>

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Distributed Adaptive Learning Tracking for Nonlinear Time-varying Multi-agent Systems With Unknown Control Directions and Dead-zone Inputs

  • 期刊论文

  • 发表日期：

    2025年9月9日

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  • Nana Yang,
  • Suoping Li,
  • Jinshu Chen,
  • Yongqiang Zhou

摘要

This paper investigates the distributed tracking problem for second-order nonlinear time-varying multi-agent systems (SONTV-MASs) subject to unknown control directions (UCDs) and input dead-zone using adaptive iterative learning control (AILC). Through parameter recombination and mean value theorem, the system is remodeled. Based on these, time-varying gains are designed to avoid the global information related topology graph and distinctive multi-Nussbaum functions are introduced. Moreover, by constructing a weighted composite energy function (WCEF), it is strictly analyzed and proved that all followers completely track the leader in a finite time interval. Numerical simulations conducted on a multi-single-link manipulator system validate the theoretical results and demonstrate the algorithm’s effectiveness.