Huimin Wang

The six‐crawler driving mechanism plays a crucial role in the operation of large machines such as bucket‐wheel excavators, dumping machines, and mobile crushing stations, as it serves functions like bearing, movement and steering. The driving characteristics of this mechanism directly influence the safety and efficiency of these machinery systems. To enhance the design methodology for multi‐crawler machinery, improve path controllability, and achieve adaptive driving, a satellite navigation control system for six‐crawler machinery was developed based on the principles of real‐time kinematic (RTK) satellite positioning. This system utilizes the distance deviation and heading angle deviation between the actual path and the predetermined path of the six‐crawler machinery as inputs to a fuzzy proportion integration differentiation (fuzzy PID) controller. This controller regulates the deviation angle of the steering crawler and the driving speeds of each track, thereby ensuring precise path tracking control. To evaluate the path tracking control performance under both straight and curved driving conditions, a virtual prototype model of the six‐crawler mechanical system was established, and co‐simulation analysis was conducted. In addition, an experimental platform for path tracking control of six‐crawler machinery was established to validate the efficacy of the satellite navigation system. The actual tracking data obtained from various driving conditions and initial deviations demonstrated that the RTK satellite navigation path tracking control system exhibited excellent control performance.

This article summarizes the research significance and the development status of the unmanned ground tracked vehicles (UGTVs). According to the speed and steering principle of the UGTVs in plane motion, the kinematic state space equation of the vehicle is established. Based on the model predictive control (MPC), the UGTVs trajectory tracking controller is also established. After introducing the overall control system solution, based on the vehicle model, the track speed on both sides is used as the control input to solve the predicted output of the system. After constraining the control amount, the model prediction controller is established by using S function. Several simulations with different preset speeds are performed under linear conditions, and the numerical simulation with different prediction time domains and control time domains are performed under continuous curves. The test validates the effectiveness of the controller, and the effects of speed and time domain parameters on the deviation are analyzed based on the results. Based on satellite positioning technology, trajectory tracking tests of the UGTVs are carried out. After analyzing the positioning principle and common errors, the real-time kinematic technology is used to improve the positioning accuracy of the vehicle prototype. The hardware of the test platform includes a data acquisition system, a control execution system and a walking execution system, and the software part includes data processing and optimization control. The trajectory tracking experiments under different driving conditions are conducted, and the results show that the navigation tracking system can achieve good tracking performance.