控制理论(社会学)
地平线
稳健性(进化)
模型预测控制
跟踪(教育)
电动汽车
计算机科学
路径(计算)
控制器(灌溉)
理论(学习稳定性)
工程类
控制(管理)
数学
人工智能
机器学习
物理
几何学
基因
功率(物理)
生物
化学
程序设计语言
量子力学
生物化学
教育学
心理学
农学
作者
Bing Zhang,Changfu Zong,Guoying Chen,Guiyuan Li
标识
DOI:10.1177/0954407018821527
摘要
An adaptive-prediction-horizon model prediction control-based path tracking controller for a four-wheel independent control electric vehicle is designed. Unlike traditional model prediction control with fixed prediction horizon, this paper devotes to satisfy the varied path tracking demand by adjusting online the prediction horizon of model prediction control according to its effect on vehicle dynamic characteristics. Vehicle dynamic stability quantized with the vehicle sideslip-feature phase plane is preferentially considered in the prediction horizon adjustment. For stability during switching prediction horizon and for robustness during path tracking, the numerical problem inherent in the adaptive-prediction-horizon model prediction control is analysed and solved by introducing exponentially decreasing weight. Subsequently, the desired motion for path tracking with the four-wheel independent control electric vehicle is realized with a hierarchical control structure. Simulation results finally illustrate the effectiveness of the proposed method.
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