Adaptive Iterative Learning Control for Nonsquare Nonlinear Multi-Agent Systems Subject to Unknown Fading Channels

• Published in: Nonlinear dynamics Vol. 113; no. 17; pp. 23083 - 23102
• Main Authors: Zeng, Dezheng, Li, Xiao-Dong, Li, Xuefang
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2025; Springer Nature B.V
• Subjects: Algorithms; Applications of Nonlinear Dynamics and Chaos Theory; Autonomous vehicles; Channels; Classical Mechanics; Communication channels; Control; Control systems; Controllers; Dynamical Systems; Fading; Learning; Multiagent systems; Network topologies; Nonlinear control; Nonlinear systems; Physics; Physics and Astronomy; Statistical Physics and Dynamical Systems; Tracking control; Vibration; Adaptive iterative learning control; Consensus tracking; Nonsquare; Unknown fading channels; Multi-agent systems
• ISSN: 0924-090X; 1573-269X
• DOI: 10.1007/s11071-025-11320-y

This paper investigates the consensus tracking control problem of nonsquare nonlinear multi-agent systems (MASs) subject to unknown fading channels. In order to compensate for the impact of the unknown fading channels, a learning-based estimation approach is proposed to estimate the unknown fading gain, based on which a novel adaptive iterative learning control (AILC) scheme is then developed to achieve the consensus tracking task in presence of system uncertainties and unknown fading channels. In contrast to the existing AILC algorithms, the proposed AILC scheme is applicable to nonsquare systems without using the invertibility property of the control gain matrices. In addition, the convergence analysis of the proposed AILC strategy is carried out with the aid of the composite energy function (CEF) method. The proposed AILC scheme is also implemented to consensus tracking of autonomous vehicles, where the effectiveness is verified.