A numerical approach for solving the inversion problem for general n-trailer systems. - Dahlmann, Julian; Völz, Andreas; Szabo, Tomas; Graichen, Knut (Proceedings 2022 American Control Conference (ACC), 2022)

A Numerical Approach for Solving the Inversion Problem for n-Trailer Systems - Dahlmann, Julian; Volz, Andreas; Szabo, Tomas; Graichen, Knut (Proceedings of the American Control Conference, 2022)
Planning feasible trajectories is a necessity for developing autonomous vehicles. This especially becomes a difficult task when arbitrary trailers are involved. This paper proposes a sequential approach to solve the inversion problem for the so-called n-trailer systems. The idea is to specify the movement of the rearmost axle and convert the vehicle chain into concatenated axle pairs. Starting from the rearmost axle, the hitching angles and their time derivatives can be computed using geometric relations as well as either numerical differentiation or integration depending on the hitching type. The algorithm constructs the vehicle motion trajectories and the required control signals. Additionally, a method for generating the reference paths is provided. The results are validated for a truck with three trailers and different hitching types.
CRIS-Team Scopus Importer:2022-10-07

Ein Konzept zum automatisierten Rangieren von Fahrzeugen mit Anhängern - Dahlmann, Julian; Graichen, Knut; Völz, Andreas (2024)

Local predictive optimization of globally planned motions for truck-trailer systems - Dahlmann, Julian; Völz, Andreas; Lukassek, Markus; Graichen, Knut (IEEE Transactions on Control Systems Technology, 2024)

Model predictive path-following control for truck–trailer systems with specific guidance points - Design and experimental validation - Lukassek, Markus; Dahlmann, Julian; Völz, Andreas; Graichen, Knut (Mechatronics, 2024)
This article presents an experimental validation of a model predictive path-following control algorithm (PF-MPC ) applied to a truck–trailer system, encompassing both forward and backward motions. The proposed controller is designed to precisely follow a predefined path generated by a path planner, with a designated guidance point positioned on either the truck or the trailer. The algorithm’s performance is assessed through implementation and validation on a model-scaled truck–trailer system, where MPC, state estimation, and low-level control are executed on a microcontroller (MCU ). The experimental results demonstrate the effectiveness of the proposed control approach in achieving highly accurate path-following performance, even when operating in the challenging context of unstable backward motion, and with the involvement of up to two trailers. Moreover, the successful implementation of the algorithm on a microcontroller underscores its suitability for real-time control applications. The results of this study collectively highlight the promising potential of the proposed control algorithm for practical utilization in autonomous driving systems.<br
Keywords: Model predictive control; Path-following control; Vehicle state estimation; Truck–trailer systems; Automotive; Microcontroller

Side-Slip Compensation in Model Predictive Path Following Control for General-n-Trailer Systems - Kögler, Philipp; Dahlmann, Julian; Graichen, Knut (28th International Conference on System Theory, Control and Computing (ICSTCC), 2024)

Trajectory optimization for truck-trailer systems based on predictive path-following control - Dahlmann, Julian; Völz, Andreas; Szabo, Tomas; Graichen, Knut (6th IEEE Conference on Control Technology and Applications (CCTA), 2022)