TY - GEN
T1 - Multiple Dynamic Targets Formation Tracking for High-Order Nonlinear Multi-Agent Systems
AU - Li, Li
AU - Zhang, Wenfei
AU - Liu, Yongfang
AU - Zhao, Yu
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The multiple dynamic targets formation tracking(MDTFT) problems for high-order nonlinear systems with undirected topologies are addressed. The aim is to make the states of multi-agents form a specified time-varying formation configuration, and to track the convex hull formed by the states of the multiple dynamic targets. Different from the well-informed agent that can obtain all the targets information in the existing papers, in this paper, a novel informed agent is considered. Agents and targets have more complex dynamical properties. To solve the MDTFT problem, a non-smooth control strategy based on signum function is proposed based on state-dependent time-varying coupling gains. The algorithm has been further improved to effectively handle the presence of an unknown bounded term in the dynamics of both the agent and the target. Simulation result is presented to illustrate the proposed algorithm.
AB - The multiple dynamic targets formation tracking(MDTFT) problems for high-order nonlinear systems with undirected topologies are addressed. The aim is to make the states of multi-agents form a specified time-varying formation configuration, and to track the convex hull formed by the states of the multiple dynamic targets. Different from the well-informed agent that can obtain all the targets information in the existing papers, in this paper, a novel informed agent is considered. Agents and targets have more complex dynamical properties. To solve the MDTFT problem, a non-smooth control strategy based on signum function is proposed based on state-dependent time-varying coupling gains. The algorithm has been further improved to effectively handle the presence of an unknown bounded term in the dynamics of both the agent and the target. Simulation result is presented to illustrate the proposed algorithm.
KW - high-order nonlinear systems
KW - informed agent
KW - Multiple dynamic targets formation tracking
UR - https://www.scopus.com/pages/publications/85189311462
U2 - 10.1109/CAC59555.2023.10450673
DO - 10.1109/CAC59555.2023.10450673
M3 - 会议稿件
AN - SCOPUS:85189311462
T3 - Proceedings - 2023 China Automation Congress, CAC 2023
SP - 2270
EP - 2275
BT - Proceedings - 2023 China Automation Congress, CAC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 China Automation Congress, CAC 2023
Y2 - 17 November 2023 through 19 November 2023
ER -