Adaptive Consensus Tracking Control for Nonlinear Multiagent Systems With Unknown Dynamics: A State Observer-Based Framework - Chen, Xiao; Li, Jinsha; Chen, Jiaxi; Li, Junmin; Chen, Weisheng (IEEE systems journal, 2025)
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.