Zero-Error Consensus Tracking With Preassignable Convergence for Nonaffine Multiagent Systems

Area of Science:

• Control Theory
• Networked Systems
• Robotics

Background:

• Consensus tracking in multiagent systems (MASs) is crucial for coordinated behavior.
• Existing methods often struggle with unknown nonaffine dynamics and require full information access.
• Achieving asymptotic consensus tracking under uncertainties with distributed control is a significant challenge.

Purpose of the Study:

• To develop a novel, fully distributed, and continuous control protocol for MASs.
• To address consensus tracking for systems with unknown nonaffine dynamics and uncertainties.
• To achieve zero-error asymptotic consensus tracking, overcoming limitations of existing approaches.

Main Methods:

• A conceptually new and structurally simple distributed control action is proposed.
• A state transformation utilizing a specific scaling function is the key technique.
• The method avoids the need for linearly parameterized information across all subsystems.

Main Results:

• The developed method ensures zero-error consensus tracking.
• A unique convergence feature is demonstrated: error first shrinks to a small residual set in finite time, then exponentially to zero.
• The protocol is fully distributed and continuous, applicable to nonlinear MASs without restrictive information requirements.

Conclusions:

• A robust and efficient solution for consensus tracking in complex MASs is presented.
• The proposed method offers a significant advancement over existing techniques for nonlinear systems.
• This work paves the way for more sophisticated coordinated control in networked systems.