Yaw stability control of automated guided vehicle under the condition of centroid variation

Abstract

The centroid of an automated guided vehicle (AGV) changes due to the irregular position and uneven weight of the cargo on the load platform, which affects the completion of the handling task between stations in intelligent factories. This paper presents a hierarchical control strategy to improve yaw stability considering centroid variation. Firstly, the vehicle body and hub motor models are established based on dynamics. Secondly a hierarchical controller is designed by using the method of extension theory, model predictive control and sliding mode control. Then based on CarSim and Simulink, the low-speed step co-simulation condition of the AGV is carried out. Compared to the uncontrolled condition, the maximum deviation of the yaw rate is reduced from 0.58 to 0.52 rad/s, and the difference with the theoretical value is reduced from 16 to 4%; the maximum deviation of the centroid sideslip angle is reduced from − 0.84 rad to − 0.77 rad, and the difference with the theoretical value is reduced from 12 to 3%. Finally, a four-wheel drive and four-wheel steering AGV are manufactured to carry out inter station steering experiments in simulated factory environment on different road adhesion coefficients. The difference between simulation and experiment is less than 5%. The results show that the designed controller is effective, and the research can provide theoretical and experimental basis for the low-speed steering control stability of AGV.