Distributed Adaptive Control of Nonlinear Multi-Agent Systems-Based Controller Dynamic Linearization Method

• Published in: IEEE Access
• Main Authors: Wenchao Wu, Lixia Fu, Han Li
• Format: Article
• Language: English
• Published: IEEE 2025-01-01
• Subjects: Data-driven control; controller dynamic linearization; multi-agent systems; distributed consensus control
• Online Access: https://ieeexplore.ieee.org/document/10962162/

The leader-follower consensus tracking control and containment control problems for nonlinear nonaffine multi input multi output (MIMO) multi-agent systems without a leader or with a leader-follower are investigated. Different from the conventional controller based compact form dynamic linearization (CFDL) method for this problem, a new distributed model free adaptive control method (CFFDL-DMFAC) is proposed by using the controller based full form dynamic linearization (CFFDL) method and a new time-varying pseudo Jacobian matrix. This method does not require a mathematical model of the system during the controller design process, and only uses real time I/O data between neighboring agents to achieve the common goal of consensus tracking of each agent. At the same time, the use of consensus error dynamic linearization methods enables the algorithm design and stability analysis of containment control to be analyzed in a unified manner with leaderless and leader-follower consensus control. Finally, rigorous mathematical proofs and simulation results are used to verify the convergence and effectiveness of the proposed control scheme.