Connectivity-Preserving Consensus Tracking of Uncertain Nonlinear Strict-Feedback Multiagent Systems: An Error...

Area of Science:

• Control Theory
• Networked Systems
• Nonlinear Dynamics

Background:

• Distributed control systems face challenges in maintaining connectivity and achieving consensus.
• Existing methods for uncertain nonlinear systems often overlook connectivity preservation.
• Limited communication ranges complicate adaptive consensus tracking in multiagent systems.

Purpose of the Study:

• To develop a distributed connectivity-preserving adaptive consensus tracking methodology.
• To address uncertain nonlinear strict-feedback multiagent systems with limited communication.
• To integrate connectivity preservation with consensus tracking for nonlinear systems.

Main Methods:

• An error-transformation-based design methodology is proposed.
• Dynamic surface control using nonlinearly transformed errors is employed.
• Neural network function approximators are utilized for local controller design.
• A technical lemma is derived for stability analysis using Lyapunov methods.

Main Results:

• The proposed method successfully preserves initial connectivity patterns.
• Adaptive consensus tracking is achieved for uncertain nonlinear systems.
• The stability of the connectivity-preserving consensus scheme is proven in the Lyapunov sense.

Conclusions:

• The presented approach offers a unified solution for connectivity preservation and consensus tracking.
• This methodology enhances the robustness of distributed control in uncertain nonlinear multiagent systems.
• The findings contribute to the advancement of reliable networked control systems.