Chalak Qazani, Mohamad Reza, Asadi, Houshyar, Shajari, Arian, Najdovski, Zoran, Lim, Chee Peng, and Nahavandi, Saeid (2023) A Development of Time-Varying Weight Model Predictive Control for Autonomous Vehicles. In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics. pp. 3480-3486. From: SMC 2023: IEEE International Conference on Systems, Man, and Cybernetics, 1-4 October 2023, Honolulu, HI, USA.

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Abstract

utonomous vehicles, commonly known as self-driving cars, are rapidly gaining popularity due to their numerous advantages, such as reducing traffic, pollution, and emissions while increasing safety, convenience, and transportation connectivity. In order to accurately track the motion signal, these vehicles are now utilising advanced control techniques, such as model predictive control (MPC). However, the efficiency of MPCs heavily relies on properly tuning their weights. The primary function of the MPC is to recalculate the optimal values for the vehicle control commands, such as desired speed, steering angle, etc., while considering the dynamic model of the autonomous vehicle. The existing linear MPC models cannot reach higher efficiency because of using fixed weights without considering the error. This paper introduces a novel approach for developing an MPC model with a time-varying weights algorithm for autonomous vehicles. The study aims to minimise motion tracking errors such as lateral position and yaw angle errors. Relevant MPC weights are calculated online using fuzzy logic-based units considering the lateral position and yaw angle errors. The proposed linear time-varying MPC was designed and developed using MATLAB software, resulting in improved motion tracking performance with 31.62% and 20.89% reduction of the root means square error of lateral position and yaw angle.

Item ID:	87049
Item Type:	Conference Item (Research - E1)
ISBN:	979-8-3503-3702-0
Copyright Information:	© 2023 IEEE
Date Deposited:	04 Sep 2025 02:37
FoR Codes:	40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400703 Autonomous vehicle systems @ 40% 40 ENGINEERING > 4007 Control engineering, mechatronics and robotics > 400705 Control engineering @ 60%
SEO Codes:	27 TRANSPORT > 2703 Ground transport > 270302 Autonomous road vehicles @ 100%
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