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

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,...

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Vydané v:International journal of control, automation, and systems Ročník 23; číslo 9; s. 2514 - 2528
Hlavní autori: Yang, Nana, Li, Suoping, Chen, Jinshu, Zhou, Yongqiang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.09.2025
Springer Nature B.V
제어·로봇·시스템학회
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ISSN:2005-4092, 1598-6446, 2005-4092
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Popis
Shrnutí: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.
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http://link.springer.com/article/10.1007/s12555-024-0649-y
ISSN:2005-4092
1598-6446
2005-4092
DOI:10.1007/s12555-024-0649-y