Distributed Formation Control: Asymptotic Stabilization Results Under Local Noisy Information.

Area of Science:

• Robotics
• Control Theory
• Distributed Systems

Background:

• Multiagent systems require coordinated control for tasks like formation flying.
• Existing methods often struggle with noise and lack of a common reference frame.

Purpose of the Study:

• To develop a reference-frame-free formation control strategy for discrete-time multiagent systems.
• To address challenges posed by measurement and communication noises.

Main Methods:

• Designed a robust distributed orientation estimation algorithm.
• Developed a robust distributed formation control law using historical data and stochastic approximation.
• Analyzed system stability under noise and specific topological conditions.

Main Results:

• Achieved asymptotic sharing of a common reference frame among agents.
• Demonstrated asymptotic stabilization of the desired formation almost surely.
• Identified critical conditions for success: bearing noise magnitude < pi/4, rooted communication/distance topology, and connected bearing topology.

Conclusions:

• The proposed distributed control law effectively enables reference-frame-free formation control in noisy environments.
• The method's success is contingent on specific noise levels and network topology.
• Simulations validate the robustness and effectiveness of the orientation estimation and control algorithms.