模型预测控制
控制理论(社会学)
卡西姆
还原(数学)
极限(数学)
工程类
维数(图论)
控制器(灌溉)
控制工程
理论(学习稳定性)
车辆动力学
计算机科学
控制(管理)
汽车工程
数学
人工智能
生物
机器学习
几何学
数学分析
纯数学
农学
作者
Wang Guo-dong,Haiping Du,Yu Meng,Li Liu,Qing Gu,Shaosong Li,Guoxing Bai
标识
DOI:10.1080/00423114.2023.2220438
摘要
In limit conditions, autonomous vehicles face the risk of lateral instability. The integrated control of steering and braking, an important measure for improving the stability of autonomous vehicles, has been extensively studied. A novel steering and braking integrated model predictive path tracking control (PTC) based on a dimension reduction model is proposed in this study. This method aims at the dilemma of the real-time limitation of the current integrated model predictive PTC based on nonlinear vehicle dynamics in practical applications and the unsatisfactory control effect of the integrated model predictive PTC based on the linearised vehicle dynamics in limit conditions. The core concept of this study is to reduce the input dimension of the integrated controller model by designing a model dimension reduction method, thereby reducing the decision variables of the optimisation problem and improving the real-time performance. The model dimension reduction method is designed based on the optimal utilisation of tire force to ensure the control performance of the proposed integrated control method in limit conditions. The integrated control method based on the dimension reduction model is compared with several existing integrated control methods in limit conditions to demonstrate its validity and superiority. The simulation tests with Simulink and CarSim indicate that the proposed method can reduce the calculation time by more than 40 % on the premise of ensuring path tracking accuracy and vehicle stability in limit conditions. Moreover, the hardware-in-the-loop tests prove the practicability of the presented method.
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