Distributed Adaptive Learning Tracking for Nonlinear Time-varying Multi-agent Systems With Unknown Control Directions and Dead-zone Inputs - Yang, Nana; Li, Suoping; Chen, Jinshu; Zhou, Yongqiang (International journal of control, automation, and systems, 2025)
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.