Research on Fuzzy Model Predictive Control Method for High Speed Intelligent Vehicles Based on Variable Universe

被引：0

作者：

He, Yang ^{[1
]}

Li, Gang ^{[1
]}

Yu, Xiaonan ^{[1
]}

机构：

[1] School of Automobile and Traffic Engineering, Liaoning University of Technology, Liaoning, Jinzhou

来源：

Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2025年 / 36卷 / 03期

关键词：

intelligent vchicle; predictive control; trajeetory tracking; variable universe;

D O I：

10.3969/j.issn.1004-132X.2025.03.024

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to improve the ability of trajeetory tracking and driving stability of high speed intelligent vehicles, a variable universe fuzzy model predictive control method(VUFMPC) was pro-posed. Based on the traditional method of trajeetory tracking model predictive control (MPC) of intelligent vehicles, a fuzzy model predictive Controller(FMPC) was established by taking the Output er-rors and the rate of change as inputs, and the adjustment factors of error weight and control increment as Outputs. For the universe inability to adaptivcly adjust, variable universe fuzzy control method (VUFC) was introduced to adaptively adjust the universe of FMPC based on Output errors. Finally, this method was verified through hand-inToop experiments. The experimentd results show that com-pared to MPC and FMPC, the maximum tracking error is redueed by 78.8% and 53.6%, the average tracking error is redueed by 38.1% and 31.6%, the optimization quantity of lateral speedy is in 52.3%~ 50.7% and 33.5%~30.9% respectively. VUFMPC reduces the tracking errors and makes driving more stable for a high speed intelligent vehicles. © 2025 Chinese Mechanical Engineering Society. All rights reserved.

引用

页码：604 / 613

页数：9

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