Research on Cooperative Control of Multiple Intelligent Networked Vehicles Based on the Improved Leader–Follower Method

Abstract

In order to study the group cooperative control method of multiple intelligent networked vehicles, the multiple intelligent networked vehicles can move in the form of a fleet. Based on the leader–follower method, the paper optimizes the control effect of the leader–follower method by solving the error transmission phenomenon in the leader–follower method. In this paper, the modeling of the multiple intelligent connected vehicle adopts the vehicle dynamics model and the Magic Formula/Swift Magic tire model, and adopts the model predictive control (MPC) dynamics trajectory tracking controller for control. Through the CarSim–Simulink multi-vehicle dynamics co-simulation platform established in this paper, the group cooperative control experiments of multiple intelligent networked vehicles under different working conditions were carried out for simulation verification. The analysis results show that the maximum average error of the proposed method decreases from 8.802 to 0.094 in the case of straight line and 0.669 to 0.379 in the case of curve tracking, which proves that the method can effectively reduce the transmission of errors.

Motion Coordination of Multiple Autonomous Mobile Robots under Hard and Soft Constraints

“…Thus, the first step is to determine the formation architecture of the fleet. Many studies have been conducted referring around the subject of the formation control of multiple mobile robots as mentioned in [6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Most of these works propose a formation based on the graph theory, meaning that they can perform from complex shapes to more simple, like a straight line (leader-follower formation).…”

“…Most of these works propose a formation based on the graph theory, meaning that they can perform from complex shapes to more simple, like a straight line (leader-follower formation). The authors in [6][7][8][9][10][11][12][13][14] propose a strategy focused on a communication network. The paper [20] introduces a unified coordinated control scheme developed for networked multi-robot systems, with a particular emphasis on object transportation.…”

“…These control laws are intended to enforce the prescribed performance attributes on the robots, assuming the absence of input constraints. Next, we design the desired velocity signals for each robot R i , i ∈ J F , that impose prescribed performance as dictated by (12) and (13). One more step that needs to be done is the calculation of the error transformation for the distance and angle of view.…”