The automated operation of articulated dump trucks (ADT) demands two control commands, one for the velocity and one for the articulation. For the velocity command, current approaches either use one constant velocity or a set of multiple constant velocities for different segments of the path. This puts a limit on the usability and performance of the control concepts since they cannot smoothly and frequently adjust the velocity depending on the driving situation. Furthermore, the consideration of the current and upcoming sideslip is the other requirement for ADT automation especially under higher velocities, which is also not thoroughly addressed in current approaches. Assuming that the trajectory is given, a trajectory following model predictive control (MPC) is presented in the course of this work, which finds the optimal solution to both steering and velocity. Furthermore, this novel approach compensates for sideslip over the prediction horizon using only the current sideslip angles. Crucial requirements expected from the MPC are that it reduces the lateral distance to the desired trajectory in comparison with other control methods, and that it stabilizes the vehicle on the trajectory without significant oscillations. Simulations of this MPC with a dynamic ADT model show a considerable improvement of the performance in terms of the maximum and overall lateral distance to the desired trajectory compared to methods that only deliver the optimal steering without sideslip consideration. The simulation environment is based on a new dynamic modeling concept, which avoids the challenging, explicit modeling of the vehicle cylinders while considering all of their effects on the vehicle movement. The simulation environment itself is also validated by comparing its results with the real full-sized vehicle data.


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    Title :

    Simulation and Successive Sideslip-Compensating Model Predictive Control for Articulated Dump Trucks


    Contributors:


    Publication date :

    2022-10-08


    Size :

    1658400 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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