Adaptive leader-follower control for nonlinear uncertain multi-agent systems with an uncertain leader and unknown...

Area of Science:

• Control Theory
• Robotics
• Networked Systems

Background:

• Leader-follower tracking is crucial for multi-agent systems.
• Existing adaptive control methods face challenges with unknown leader parameters and uncertain tracking paths.

Purpose of the Study:

• To develop a robust adaptive control strategy for leader-follower tracking in multi-agent networks.
• To address uncertainties in followers, including unknown parameters, nonlinearities, disturbances, communication weights, and sensor faults.

Main Methods:

• Designed distributed adaptive observers to estimate the leader's tracking path.
• Developed local adaptive observers to estimate individual follower states.
• Implemented distributed adaptive controllers using estimated states and the tracking path.

Main Results:

• Sufficient conditions for tracking performance were established for both observers and controllers.
• The proposed methods demonstrated efficacy in common literature examples.
• The adaptive approaches proved effective in handling various uncertainties.

Conclusions:

• The study successfully solved the challenging leader-follower tracking problem under significant uncertainties.
• The proposed distributed adaptive control framework enhances the robustness and applicability of multi-agent systems.