Bounded Intermittent Control And Experiment Of Multi-agent Formation Tracking

Multi-agents have a wide range of application scenarios at present and in the future.As a control method of agents,intermittent control has significant advantages in reducing energy consumption and enhancing the usability of multi-agents.With the continuous expansion of the scale of multi-agent networks,the use of intermittent control to optimize multi-agent networks,reduce energy consumption and enhance the practical performance of multi-agent networks has also become a recent research hotspot.This paper studies the related problems of bounded intermittent control of multi-agent tracking formation.Based on the first-order and second-order multi-agent dynamics models respectively,the bounded intermittent control law and its system stability conditions are given by using boundary functions,adaptive estimation and switching system theory.Finally,MATLAB simulation,gazebo physical simulation and ROS experimental platform were used to verify the designed algorithm.This article mainly completed the following work:1.Aiming at the formation tracking control problem of the multi-agent system described by the first-order integrator,a new intermittent control method is proposed,and the duty cycle conditions of the control cycle when the system is stable are given.On this basis,the control input is further considered to be bounded,and the average value theory,adaptive estimation method and Lyapunov stability theory are combined to prove the stability of the system.Finally,the simulation results verify the correctness of the relevant conclusions.2.For the intermittent control problem of the bounded formation tracking of the multi-agent system described by the second-order integrator.Based on the first-order multi-agent system,a new definition of the boundary function is further given.At the same time,based on the Lyapulov stability theorem,the system’s stable cycle duty cycle conditions and the design of the corresponding control parameters are proved.Finally,the correctness of the relevant theories is verified by simulation.3.Simulation experiment verification based on ROS system.First verify the above-mentioned related algorithms in the gazebo physical simulation platform.By combining the UWB indoor positioning equipment and the odometer in the robot chassis to obtain the actual position information,the control algorithm is further transplanted to the actual robot.Simulation and experimental results also show the effectiveness of the designed algorithm.