Article: High-speed trajectory following of a heavy-duty vehicle via adaptive nonlinear model predictive controller Journal: International Journal of Vehicle Performance (IJVP) 2024 Vol.10 No.2 pp.119 - 143 Abstract: In this paper, a controller based on novel discrete-time adaptive nonlinear model predictive control (AN-MPC) is proposed to enhance the trajectory tracking performance of a heavy-duty vehicle preventing the wheel lift-off and lateral slip, increasing maximum NATO double lane change (DLC) speed. An eight-DOF nonlinear vehicle model is designed as a system model to obtain the realistic behaviour of the vehicle. This model is experimentally validated by using the data obtained in NATO DLC tests. The proposed controller is based on a two-DOF nonlinear single-track vehicle model and configured to be adaptive in two aspects: linearisation of the base model at each sampling instant and online tuning of the controller parameters. The tuning process is achieved by an artificial-neural-network structure. The simulated results revealed that the DLC speeds can be significantly improved due to the predictive capability of the proposed controller, compared to the classical PID controllers or human drivers. Inderscience Publishers - linking academia, business and industry through research

Title: High-speed trajectory following of a heavy-duty vehicle via adaptive nonlinear model predictive controller

Authors: Volkan Bekir Yangin; Ozgen Akalin; Yaprak Yalcin

Addresses: Department of Mechanical Engineering, Faculty of Mechanical Engineering, Istanbul Technical University, Beyoglu, Istanbul, 34437, Turkey ' Department of Mechanical Engineering, Faculty of Mechanical Engineering, Istanbul Technical University, Beyoglu, Istanbul, 34437, Turkey ' Department of Control and Automation Engineering, Faculty of Electrical and Electronics Engineering, Istanbul Technical University, Sariyer, Istanbul, 34469, Turkey

Abstract: In this paper, a controller based on novel discrete-time adaptive nonlinear model predictive control (AN-MPC) is proposed to enhance the trajectory tracking performance of a heavy-duty vehicle preventing the wheel lift-off and lateral slip, increasing maximum NATO double lane change (DLC) speed. An eight-DOF nonlinear vehicle model is designed as a system model to obtain the realistic behaviour of the vehicle. This model is experimentally validated by using the data obtained in NATO DLC tests. The proposed controller is based on a two-DOF nonlinear single-track vehicle model and configured to be adaptive in two aspects: linearisation of the base model at each sampling instant and online tuning of the controller parameters. The tuning process is achieved by an artificial-neural-network structure. The simulated results revealed that the DLC speeds can be significantly improved due to the predictive capability of the proposed controller, compared to the classical PID controllers or human drivers.

Keywords: vehicle dynamics; lateral stability; maximum speed; trajectory tracking; steering angle control; model predictive control; MPC.

DOI: 10.1504/IJVP.2024.137675

International Journal of Vehicle Performance, 2024 Vol.10 No.2, pp.119 - 143

Received: 23 Mar 2023
Accepted: 27 Jul 2023
Published online: 02 Apr 2024 *

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Title: High-speed trajectory following of a heavy-duty vehicle via adaptive nonlinear model predictive controller

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