| Trajectory Tracking Control of Intelligent Vehicles Based on Integrated MPC with Fuzzy Adaptive Weighting |
| Yao-hua Li, Guo-qing Dong, Jiang-wu Wang, Mao-meng Li, Zi-chen Wang, Qin-zhen Wang, Wei-chao Guo |
| School of Automotive, Chang’an University, Xi’an, 710064, China |
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Received: November 13, 2024; Revised: February 27, 2025 Accepted: March 13, 2025. Published online: April 28, 2025. |
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| ABSTRACT |
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The centralized Model Predictive Control (MPC) trajectory tracking controllers are designed to comprehensively consider lateral and longitudinal motion aiming for the separated control of lateral and longitudinal motion of intelligent vehicle. Aiming for the design and adjustment of multi-weighing factors caused by multi-object control, the weighting adaptive controller based on fuzzy control is proposed, whose inputs are lateral deviation, heading deviation, longitudinal deviation and speed deviation and outputs are lateral error weight, heading error weight, and position error weight. The simulation results show that under variable-speed double lane change trajectory tracking control, the trajectory tracking based on integrated MPC with fuzzy adaptive weighting can improve lateral and longitudinal tracking accuracy by 11% and 22% at high adhesion coefficient road, and by 46% and 70% at low adhesion coefficient road. |
| Key Words:
Autonomous driving · Trajectory tracking control · Model predictive control · Weighting factor · Fuzzy control |
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Corresponding Author.
Yao-hua Li , Email. 
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