Distributed Sliding-Mode Tracking Control of Second-Order Nonlinear Multiagent Systems: An Event-Triggered Approach

Area of Science:

• Control Systems Engineering
• Robotics and Automation
• Networked Systems

Background:

• Multiagent systems (MAS) are crucial for complex tasks, but traditional control methods face challenges with communication bandwidth and system nonlinearities.
• Event-triggered control strategies offer a promising solution to reduce communication load by updating controllers only when necessary.
• Sliding-mode control (SMC) is a robust technique for handling nonlinearities and uncertainties in dynamic systems.

Purpose of the Study:

• To investigate the event-triggered tracking control problem for second-order multiagent systems with system nonlinearities.
• To develop a distributed sliding-mode control (SMC) approach that incorporates an event-triggered strategy.
• To ensure consensus tracking performance and reduce communication resource usage in leader-following multiagent systems.

Main Methods:

• A distributed event-based sliding-mode controller was designed for second-order multiagent systems.
• A novel integral sliding-mode surface was constructed to handle system nonlinearities and guarantee consensus.
• The Lyapunov approach was employed to derive sufficient conditions for closed-loop system stability and performance.
• An event-triggered strategy was established to minimize controller sampling frequency and communication overhead.

Main Results:

• The proposed controller enables the system state to approach the integral sliding-mode surface in finite time.
• Consensus tracking performance is guaranteed in the presence of system nonlinearities.
• The event-triggered scheme effectively reduces state updates and eliminates Zeno behavior.
• Simulation results validate the efficacy of the proposed methodology.

Conclusions:

• The developed event-triggered distributed SMC effectively addresses the tracking control problem in nonlinear second-order multiagent systems.
• The strategy significantly conserves network communication resources by reducing controller sampling frequency.
• The method ensures robust consensus tracking performance and avoids undesirable Zeno behavior, demonstrating practical applicability.