Command filter based adaptive fuzzy bipartite output consensus tracking of nonlinear coopetition multi-agent systems...

Area of Science:

• Control Theory
• Artificial Intelligence
• Systems Engineering

Background:

• Coopetition multi-agent systems (MAS) exhibit complex dynamics, requiring advanced control strategies.
• Input saturation and nonlinearities pose significant challenges in achieving consensus tracking.
• Existing methods often struggle with adaptive control under these constraints.

Purpose of the Study:

• To develop a distributed adaptive control scheme for bipartite output consensus tracking.
• To address high-order nonlinear coopetition MAS with input saturation.
• To ensure stability and convergence of tracking errors in complex systems.

Main Methods:

• A distributed fuzzy logic system (FLS) based command filtered backstepping approach is proposed.
• FLS are utilized to approximate unknown nonlinear dynamics within each agent.
• An error compensation mechanism is designed to mitigate filter-induced errors.

Main Results:

• The proposed control scheme ensures bipartite output tracking errors converge to a small neighborhood.
• All closed-loop signals remain bounded, even in the presence of input saturation.
• Only one adaptive law per agent is required, simplifying controller design.

Conclusions:

• The fuzzy-based command filtered backstepping scheme effectively solves the adaptive bipartite output consensus tracking problem.
• The approach demonstrates robustness against input saturation in nonlinear coopetition MAS.
• Numerical examples validate the proposed control scheme's effectiveness.