适应性
稳健性(进化)
主动安全
控制理论(社会学)
控制工程
工程类
滑模控制
控制系统
电子稳定控制
计算机科学
PID控制器
人工神经网络
防抱死制动系统
非线性系统
算法
制动器
控制(管理)
汽车工程
人工智能
温度控制
生态学
生物化学
化学
物理
电气工程
量子力学
生物
基因
作者
Shuaiwei Zhu,Xiaobin Fan,Gengxin Qi,Pan Wang
标识
DOI:10.2174/1872212116666220324154143
摘要
Background: Automobile anti-lock braking system (ABS) is an important part of the vehicle active safety control system, which is widely used in all kinds of vehicles. At present, the research of ABS mainly focuses on the study of the control algorithm, which is intended to improve the stability, robustness, and adaptability of the control algorithm. Objective: In the future, it is necessary to explore adaptive robust control algorithms that adapt to extreme conditions such as high nonlinearity and sudden road changes, such as active disturbance rejection control technology, deep learning neural network control technology, etc. Method: According to the research status of domestic and foreign researchers in the field of ABS control algorithms, ABS control algorithms are mainly divided into two categories: control methods based on logic thresholds and control methods based on slip ratio. Results: The comparative study of ABS control methods shows that the logic threshold control method has strong maneuverability and simple implementation, but its adaptability is poor. Sliding mode control has strong robustness and good transient response, but chattering needs to be suppressed. Although the PID control algorithm is simple and easy to implement, it needs to improve the transient response of the system.
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