Distributed Time-Varying Formation Control With Obstacle Avoidance of Multiagent Systems Under Switching Topologies

Area of Science:

• Robotics and Control Systems
• Distributed Systems
• Artificial Intelligence

Background:

• Multiagent systems (MASs) face challenges in coordinated movement, especially with unpredictable environmental factors.
• Existing formation tracking control methods often struggle with obstacle avoidance and dynamic system changes.

Purpose of the Study:

• To develop a robust distributed formation tracking control strategy for MASs with obstacle avoidance.
• To address challenges posed by random switching topologies and external disturbances.

Main Methods:

• A three-step control strategy integrating transition probability (TP)-based mode-dependent average dwell-time (MDADT) switching topologies.
• Design of a safe objective trajectory by projecting unsafe path segments onto obstacle boundaries.
• Proposal of an integral-multiplicative barrier Lyapunov function (IMBLF) for safe trajectory tracking.

Main Results:

• Achieved almost sure global exponential tracking of desired formation trajectories under MDADT switching.
• Successfully implemented obstacle avoidance by generating safe objective trajectories.
• Demonstrated the effectiveness of IMBLF in guaranteeing MAS safety without impulsive Lyapunov function increases.

Conclusions:

• The proposed control strategy offers a feasible and effective solution for distributed formation tracking with obstacle avoidance in MASs.
• The IMBLF approach eliminates the need for classical analysis methods' impulsive Lyapunov function increases, simplifying analysis.
• Simulation results verified the method's performance in complex, dynamic environments.