Distributed Adaptive Formation Tracking for a Class of Uncertain Nonlinear Multiagent Systems: Guaranteed...

Area of Science:

• Robotics
• Control Systems
• Network Engineering

Background:

• Multiagent systems require robust formation tracking and collision avoidance.
• Maintaining network connectivity is crucial during dynamic obstacle interactions.
• Uncertainties in nonlinear systems and range constraints pose significant challenges.

Purpose of the Study:

• To address guaranteed network connectivity during moving obstacle avoidance.
• To develop an adaptive distributed control framework for uncertain nonlinear multiagent systems.
• To ensure stable formation tracking while preserving communication links.

Main Methods:

• Utilized nonlinear error variables for formation tracking and collision avoidance.
• Introduced auxiliary signals within formation tracking errors to maintain network connectivity.
• Employed command-filtered backstepping for adaptive formation controllers and Lyapunov-based design.

Main Results:

• Developed an adaptive tuning mechanism for estimating dynamic obstacle velocities.
• Successfully preserved network connectivity during dynamic obstacle avoidance maneuvers.
• Achieved closed-loop stability with collision avoidance and maintained connectivity without bounding virtual controller derivatives.

Conclusions:

• The proposed adaptive distributed design guarantees network connectivity in multiagent systems with moving obstacles.
• The method enhances robustness in uncertain nonlinear systems under range constraints.
• This framework offers a novel approach to collision avoidance and communication preservation in multiagent robotics.