Adaptive Compensation for Nonlinear Time-Varying Multiagent Systems With Actuator Failures and Unknown Control...

Area of Science:

• Control Theory
• Robotics
• Systems Engineering

Background:

• Multiagent systems are crucial in various fields but susceptible to actuator failures and control uncertainties.
• Designing cooperative control for nonlinear, time-varying systems with unknown parameters remains a significant challenge.

Purpose of the Study:

• To develop an adaptive asymptotic cooperative control scheme for nonlinear time-varying multiagent systems.
• To address simultaneous unknown actuator failures and unknown control directions.
• To ensure robust performance and asymptotic convergence of followers to the leader.

Main Methods:

• A conditional inequality is proposed to enhance control robustness using piecewise Nussbaum functions.
• Adaptive control techniques are employed to compensate for remaining uncertainties and system errors.
• Structural properties of adaptive laws are leveraged with Barbalat's lemma for convergence analysis.

Main Results:

• The proposed scheme effectively tolerates unknown actuator failures and control direction uncertainties.
• Partial uncertainties and system errors are compensated through inherent robustness.
• The remaining uncertainties are managed by the adaptive control, ensuring follower convergence.

Conclusions:

• The developed adaptive cooperative control scheme guarantees asymptotic convergence for multiagent systems under challenging conditions.
• The approach provides a robust solution for practical applications involving unreliable actuators and unknown system dynamics.