Containment Control of Linear Multiagent Systems With Aperiodic Sampling and Measurement Size Reduction

Area of Science:

• Control Systems Engineering
• Networked Systems
• Robotics

Background:

• Multiagent systems face challenges in containment control due to aperiodic sampling and communication constraints.
• Existing protocols often require fixed or limited sampling intervals, hindering efficiency.

Purpose of the Study:

• To develop an improved containment control protocol for linear multiagent systems.
• To address challenges posed by aperiodic sampling intervals and measurement size reduction.
• To enhance communication efficiency among agents.

Main Methods:

• Proposed an improved protocol allowing variable, larger sampling intervals from a finite set.
• Transformed the containment control problem into a discrete-time switched linear system stability problem.
• Utilized Laplacian matrix properties and linear matrix inequalities (LMIs) for analysis.

Main Results:

• Derived a sufficient condition for follower convergence to the leaders' convex hull.
• The condition is presented as LMIs, independent of network topology.
• Introduced a switching-type measurement size reduction scheme to minimize communication.

Conclusions:

• The proposed control algorithms effectively achieve containment control in multiagent systems.
• The approach allows for larger sampling intervals and reduced communication, enhancing system performance.
• Simulation studies validate the effectiveness and advantages of the developed control strategies.