Cooperative Control for Stochastic Multiagent Systems With Deferred Dynamic Constraints via a Novel Universal Barrier...

Area of Science:

• Control Theory
• Systems Engineering
• Robotics

Background:

• Stochastic multiagent systems (MASs) present complex control challenges, especially with dynamic constraints.
• Existing control methods often require strict feasibility conditions or struggle with deferred full-state constraints.

Purpose of the Study:

• To develop a robust cooperative control strategy for stochastic MASs with dynamic constraints.
• To design a universal barrier function applicable to diverse constraint types, including unconstrained systems.
• To achieve precise tracking control with guaranteed finite-time convergence.

Main Methods:

• A novel universal barrier function and mapping functions are proposed to handle state variable constraints.
• The backstepping framework is employed for controller design.
• An improved funnel error transformation and a deferred funnel controller with a finite-time function are developed.

Main Results:

• The proposed control algorithm effectively constrains state variables without prior feasibility conditions.
• Tracking errors are maintained within a predetermined funnel in finite time.
• The convergence time is adjustable and independent of controller parameters and initial conditions.

Conclusions:

• The developed control strategy offers a versatile and effective solution for cooperative control of stochastic MASs with dynamic constraints.
• The universal barrier function and deferred funnel controller significantly enhance tracking precision and convergence properties.
• Simulation results validate the effectiveness and robustness of the proposed control algorithm.