Consensus conditions for heterogeneous multi-agent sampled-data control systems with nonlinearities and inter-agent...

Area of Science:

• Control Systems Engineering
• Robotics
• Networked Systems

Background:

• Heterogeneous nonlinear multi-agent systems (MASs) face challenges in achieving consensus due to sampled-data control and communication delays.
• Existing methods often struggle with computational complexity and conservatism when dealing with these heterogeneous dynamics and delays.

Purpose of the Study:

• To develop a robust control strategy for achieving consensus in heterogeneous nonlinear MASs under sampled-data control with inter-agent communication delays.
• To propose a novel Lyapunov-Krasovskii functional that effectively handles both sampling and network-induced delays while minimizing conservatism.

Main Methods:

• A two-sided looped Lyapunov-Krasovskii functional is introduced to analyze system stability.
• The framework unifies heterogeneous network delays and distinguishes between state sampling and control update instants to reduce computational complexity.
• Analysis of variable influence on performance and computational load is conducted.

Main Results:

• The proposed approach effectively addresses the consensus problem in heterogeneous nonlinear MASs.
• Conservatism is reduced, and scalability is enhanced through the unified treatment of delays and distinct sampling/update instants.
• Simulations demonstrate practical feasibility on a multi-agent system of brushed DC motors.

Conclusions:

• The developed sampled-data control strategy provides a scalable and less conservative solution for consensus problems in heterogeneous nonlinear MASs.
• The novel looped Lyapunov-Krasovskii functional is effective in managing complex delay dynamics.
• The approach is validated for practical applications like robotic systems coordination.