Distributed estimation and control for nonlinear multi-agent systems in the presence of input delay or external...

Area of Science:

• Control Systems Engineering
• Robotics
• Networked Systems

Background:

• Multi-agent systems (MASs) face challenges in coordinated control due to external disturbances and communication delays.
• Tracking control (TC) is crucial for MASs to follow dynamic targets accurately.
• Existing methods often struggle with nonlinear dynamics and unpredictable environmental factors.

Purpose of the Study:

• To develop robust distributed algorithms for nonlinear multi-agent systems (MASs) to solve the tracking control (TC) problem.
• To address challenges posed by external disturbances and time delays in MASs.
• To ensure stable and accurate target tracking for each agent in the system.

Main Methods:

• A distributed controller is designed using a distributed observer for agents to estimate and follow a nonlinear target.
• A future predictor (FP) and an external disturbance observer are integrated into the controller to handle delays and disturbances.
• Stability analysis of control laws and the FP is performed, with sufficient conditions derived for TC in MASs.

Main Results:

• The proposed distributed algorithms effectively enable agents to perform tracking control under external disturbances and delays.
• Stability of the developed control laws and future predictor is mathematically proven.
• Simulation results demonstrate the efficiency and robustness of the presented TC methods for MASs.

Conclusions:

• The developed distributed algorithms provide a robust solution for tracking control in nonlinear multi-agent systems facing disturbances and delays.
• The integration of future predictors and disturbance observers enhances the system's ability to maintain accurate tracking.
• The findings offer a valuable contribution to the field of distributed control for complex multi-agent applications.