Adaptive Consensus Tracking Control for Nonlinear Multiagent Systems With Unknown Dynamics: A State Observer-Based Framework

• Published in: IEEE systems journal Vol. 19; no. 2; pp. 447 - 458
• Main Authors: Chen, Xiao, Li, Jinsha, Chen, Jiaxi, Li, Junmin, Chen, Weisheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Backstepping; consensus algorithm; Control systems; Dynamical systems; Feedback control systems; Fuzzy logic; Fuzzy systems; Multi-agent systems; Multiagent systems; Nonlinear control; Nonlinear dynamical systems; Nonlinear dynamics; nonlinear multiagent systems (MASs); Nonlinear systems; Observers; Output feedback; Process control; Simulation; state observer; State observers; Topology; Tracking control; Uncertainty; unknown control directions; Vectors
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2025.3562957

In this study, we introduce an observer-based adaptive output-feedback tracking consensus approach designed for a class of uncertain nonlinear leader-follower multiagent systems. Each follower agent exhibits second-order unknown nonlinear dynamics, incorporates unmeasured states, and possesses an unknown control direction. To tackle these challenges, fuzzy logic system is integrated with an observer, and a Nussbaum-type item is integrated into the protocol for each agent to adaptively and cooperatively determine the control direction. Subsequently, we have developed adaptive fuzzy distributed control protocols for each follower agent. The proposed consensus protocols have been demonstrated to ensure semiglobally uniformly ultimate boundedness for all system signals. Furthermore, we extend the control gain from constant to a state-dependent gain, delving into the globally uniformly ultimate boundedness of multiagent systems. To mitigate the intricacies arising from virtual control differentiation, command filtering is integrated with backstepping techniques, thereby streamlining the control process and enhancing overall system performance. The efficacy of the proposed method has been validated through simulation examples.