Multiple Intentional Delays Can Facilitate Fast Consensus and Noise Reduction in a Multiagent System

Area of Science:

• Control Theory
• Robotics
• Networked Systems

Background:

• Achieving fast consensus in large-scale multiagent systems is challenging.
• Traditional controllers can be sensitive to noise, impacting performance.
• Derivative-based controllers require accurate velocity measurements, which are often noisy.

Purpose of the Study:

• To develop a derivative-free control scheme for efficient consensus.
• To mitigate noise effects by relying solely on position measurements.
• To enable fast and stable convergence in multiagent systems.

Main Methods:

• Utilizing a multiple-delay proportional-retarded (PR) control protocol.
• Intentionally introducing delays to create derivative-like control actions.
• Analyzing consensus dynamics through spectral abscissa and separation.

Main Results:

• Successfully placed the spectral abscissa of consensus dynamics at a desired locus.
• Achieved user-defined spectral separation, directly influencing convergence.
• Demonstrated the effectiveness of the PR protocol through case studies.

Conclusions:

• The multiple-delay PR protocol offers a robust and effective method for achieving fast consensus.
• The derivative-free approach enhances system stability by reducing noise sensitivity.
• Analytical design rules and limitations provide a framework for practical implementation.