Research on Automatic Driving Control of Tracked Transport Vehicle Based on Labview

Abstract

HighlightsAn indirect Kalman filter algorithm is proposed to fuse GNSS/INS positioning information.Detailed kinematics and dynamics model of track vehicles was established.An MPC-based double-layer closed-loop controller combined with tracked vehicle model is designed.Tracked transport vehicle performs well in path tracking on soft soil road.Abstract. Orchards in hills and mountainous regions are more occluded and single satellite navigation is unstable. Therefore, the indirect Kalman filter information fusion algorithm was proposed to achieve high-precision positioning by establishing a state error equation based on GNSS/INS. A complete kinematics and dynamics model of tracked chassis was established. A double-layer closed-loop controller based on model predictive control (MPC) was designed. An MPC controller based on the kinematics model in the outer loop was designed to output the expected control value of the tracked transporter. The inner loop design was based on the extended state observer of the dynamic model to estimate and compensate for the internal and external disturbances of the system. The performance test was based on a tracked chassis platform. The test results presented that when driving at a speed of 0.50 m/s under soft soil road conditions, the maximum lateral deviation was 0.15 m, and the average absolute deviation was 0.05 m. This high level of control accuracy means that this control design enables the transfer vehicle to follow the navigation path precisely and complete its task. Keywords: Hills and mountainous regions, Integrated navigation, Model predictive control, Vehicle dynamics model.