Event-Triggered/Self-Triggered Leader-Following Control of Stochastic Nonlinear Multiagent Systems Using High-Gain...

Area of Science:

• Control Systems Engineering
• Nonlinear Systems Theory
• Stochastic Processes

Background:

• Investigates leader-following output-feedback control for high-order stochastic nonlinear multiagent systems (MASs).
• Addresses challenges in state estimation and distributed control under undirected graph topologies.

Purpose of the Study:

• To develop event-triggered and self-triggered control strategies for enhanced MAS performance.
• To design a Zeno-free dynamic event-triggered controller and a Zeno-free self-triggering mechanism.
• To improve control efficiency by prolonging interevent times and reducing continuous state monitoring.

Main Methods:

• Employs the high-gain method for observer design to estimate unmeasured state variables.
• Introduces an internal dynamic variable to construct a distributed Zeno-free dynamic event-triggered controller.
• Proposes a Zeno-free self-triggering mechanism to avoid continuous state monitoring.

Main Results:

• The dynamic event-triggering mechanism prolongs interevent time compared to static methods, enhancing control advantages.
• Demonstrates convergence of output tracking errors to a small set when diffusion terms differ among agents.
• Shows convergence of state tracking errors to a small set when diffusion terms are identical across agents.

Conclusions:

• The proposed event-triggered and self-triggered control methods are effective for high-order stochastic nonlinear MASs.
• Simulation studies validate the practical applicability and performance of the developed control strategies.