Chen, Xuanwei and Cheng, Jiaqi and Hu, Huosheng and Shao, Guifang and Gao, Yunlong and Zhu, Qingyuan (2024) A Novel Fuzzy Logic Switched MPC for Efficient Path Tracking of Articulated Steering Vehicles. Robotics, 13 (9). p. 134. DOI https://doi.org/10.3390/robotics13090134
Chen, Xuanwei and Cheng, Jiaqi and Hu, Huosheng and Shao, Guifang and Gao, Yunlong and Zhu, Qingyuan (2024) A Novel Fuzzy Logic Switched MPC for Efficient Path Tracking of Articulated Steering Vehicles. Robotics, 13 (9). p. 134. DOI https://doi.org/10.3390/robotics13090134
Chen, Xuanwei and Cheng, Jiaqi and Hu, Huosheng and Shao, Guifang and Gao, Yunlong and Zhu, Qingyuan (2024) A Novel Fuzzy Logic Switched MPC for Efficient Path Tracking of Articulated Steering Vehicles. Robotics, 13 (9). p. 134. DOI https://doi.org/10.3390/robotics13090134
Abstract
This paper introduces a novel fuzzy logic switched model predictive control (MPC) algorithm for articulated steering vehicles, addressing significant path tracking challenges due to varying road conditions and vehicle speeds. Traditional single-model and parameter-based controllers struggle with tracking errors and computational inefficiencies under diverse operational conditions. Therefore, a kinematics-based MPC algorithm is first developed, showing strong real-time performance but encountering accuracy issues on low-adhesion surfaces and at high speeds. Then, a 4-DOF dynamics-based MPC algorithm is designed to enhance tracking accuracy and control stability. The proposed solution is a switched MPC strategy, integrating a fuzzy control system that dynamically switches between kinematics-based and dynamics-based MPC algorithms based on error, solution time, and heading angle indicators. Subsequently, simulation tests are conducted using SIMULINK and ADAMS to verify the performance of the proposed algorithm. The results confirm that this fuzzy-based MPC algorithm can effectively mitigate the drawbacks of single-model approaches, ensuring precise, stable, and efficient path tracking across diverse adhesion road conditions.
Item Type: | Article |
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Uncontrolled Keywords: | articulated steering vehicles; path tracking; model predictive control; fuzzy logic control; diverse adhesion road conditions |
Divisions: | Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 12 Sep 2024 16:07 |
Last Modified: | 12 Sep 2024 16:07 |
URI: | http://repository.essex.ac.uk/id/eprint/39140 |
Available files
Filename: Robotics-V13-I9-134-2024.pdf
Licence: Creative Commons: Attribution 4.0