Distributed Finite-Time Containment Control for Nonlinear Multiagent Systems With Mismatched Disturbances

Area of Science:

• Control Systems Engineering
• Robotics
• Networked Systems

Background:

• Multiagent systems are crucial for distributed tasks but face challenges from uncertainties and failures.
• Achieving coordinated behavior (containment) in these systems under adverse conditions is complex.

Purpose of the Study:

• To develop a finite-time adaptive containment control scheme for uncertain nonlinear multiagent systems.
• To address mismatched disturbances and actuator failures within the control framework.
• To enhance computational efficiency compared to existing methods.

Main Methods:

• Modified dynamic surface control and adding a power integrator techniques for algorithm development.
• Backstepping-based disturbance observers to handle mismatched uncertainties.
• Adaptive compensation strategies for loss-of-effectiveness and lock-in-place actuator fault models.

Main Results:

• A distributed finite-time adaptive containment algorithm with reduced computational load was designed.
• Disturbance observers effectively compensated for system uncertainties.
• The proposed scheme demonstrated practical finite-time stability of containment errors, even with actuator faults.

Conclusions:

• The developed finite-time adaptive containment control scheme is effective for uncertain nonlinear multiagent systems.
• The approach successfully handles mismatched disturbances and various actuator failures.
• Simulation results validate the theoretical findings and practical applicability.