Adaptive Fuzzy Output-Feedback Consensus Tracking Control of Nonlinear Multiagent Systems in Prescribed Performance

Area of Science:

• Control Theory
• Nonlinear Systems
• Multiagent Systems

Background:

• Consensus tracking is crucial for coordinated behavior in multiagent systems (MASs).
• Handling unmeasured states and unknown nonlinearities in MASs presents significant control challenges.
• Existing finite/fixed-time control methods often lack precise control over settling time and convergence region.

Purpose of the Study:

• To develop an observer-based adaptive fuzzy consensus tracking controller for nonlinear MASs.
• To address challenges posed by unmeasured state variables and unknown nonlinear functions.
• To guarantee finite-time convergence of consensus tracking errors within a pre-specified region.

Main Methods:

• Design of an observer to estimate unmeasured state variables.
• Utilization of fuzzy-logic systems for approximating unknown nonlinear functions.
• Application of the backstepping technique combined with a novel barrier Lyapunov function.

Main Results:

• The proposed control protocol ensures all closed-loop system signals remain bounded.
• Consensus tracking errors converge to a pre-specified region around the origin in finite time.
• Settling time and convergence region are designer-adjustable and independent of unknown system constants.

Conclusions:

• The developed observer-based adaptive fuzzy controller effectively achieves finite-time consensus tracking for nonlinear MASs.
• The controller offers superior performance by allowing pre-assignment of settling time and convergence bounds.
• Simulation examples validate the practical applicability and effectiveness of the proposed control scheme.