Observer-Based Fuzzy Adaptive Finite-Time Containment Control of Nonlinear Multiagent Systems With Input Delay

Area of Science:

• Control Theory
• Nonlinear Systems
• Multiagent Systems

Background:

• Finite-time containment control is crucial for coordinating multiagent systems.
• Unknown nonlinear dynamics and time delays present significant challenges.
• State information is often unavailable for control design.

Purpose of the Study:

• To develop a finite-time containment control strategy for nonlinear multiagent systems.
• To address challenges of unknown nonlinearities, unmeasured states, and time delays.
• To ensure followers converge to the convex hull of leaders within a finite time.

Main Methods:

• Fuzzy-logic systems (FLSs) for approximating unknown nonlinear functions.
• A novel distributed fuzzy state observer to estimate unmeasured states.
• Adaptive backstepping control design with an integral compensator.
• Finite-time Lyapunov function theory for stability analysis.

Main Results:

• An observer-based adaptive fuzzy finite-time output-feedback containment control scheme was developed.
• The proposed method guarantees closed-loop system stability.
• All follower agents converge to the convex hull formed by the leader agents in finite time.

Conclusions:

• The adaptive fuzzy containment control method effectively solves the finite-time containment control problem.
• The approach handles nonlinearities, unmeasured states, and time delays robustly.
• Simulation results validate the proposed control strategy's effectiveness.