基于RBF网络滑模的电动助力制动系统液压力控制

doi:10.3901/JME.2020.24.106

机械工程学报 ›› 2020, Vol. 56 ›› Issue (24): 106-114.doi: 10.3901/JME.2020.24.106

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基于RBF网络滑模的电动助力制动系统液压力控制

赵健, 邓志辉, 朱冰, 常婷婷, 陈志成

吉林大学汽车仿真与控制国家重点实验室长春 130022

收稿日期:2020-01-02 修回日期:2020-06-06 出版日期:2020-12-20 发布日期:2021-02-05
通讯作者: 朱冰(通信作者),男,1982年出生,博士,教授,博士研究生导师。主要研究方向为汽车电控与智能化,智能汽车人机共驾理论。E-mail:zhubing@jlu.edu.cn
作者简介:赵健,男,1978年出生,博士,教授,博士研究生导师。主要研究方向为汽车集成化与智能化,电子线控制动系统设计与控制。E-mail:zhaojian@jlu.edu.cn;邓志辉,男,1994年出生。主要研究方向为汽车底盘电控与智能化。E-mail:1342860247@qq.com
基金资助:
国家自然科学基金（51775235、51575225）、吉林省科技发展计划重点科技研发（20180201056GX）和吉林省发改委预算内基本建设资金（2019C036-6）资助项目。

Sliding Mode Control Based on RBF Network for Hydraulic Pressure in Electric Power-assisted Brake System

ZHAO Jian, DENG Zhihui, ZHU Bing, CHANG Tingting, CHEN Zhicheng

State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022

Received:2020-01-02 Revised:2020-06-06 Online:2020-12-20 Published:2021-02-05

摘要/Abstract

摘要： 针对汽车电动助力制动系统（Electro-booster，EBooster）的液压力控制中液压负载的非线性和不一致性问题，提出一种基于径向基函数（Radial based function，RBF）神经网络的滑模变结构控制方法。设计EBooster系统压力控制架构，建立液压制动系统等效结构简化模型，据此设计基于RBF网络滑模变结构的液压力控制方法，通过设计RBF网络的自适应律来实现系统滑模控制参数的自适应调整，并利用李雅普诺夫函数方法分析算法的稳定性。最后搭建电动助力制动系统的快速原型试验平台来验证算法的有效性。试验结果表明，采用RBF神经网络滑模变结构的控制策略对电动助力制动系统液压力的控制误差在2%以内，具有良好的控制效果。研究成果为EBooster系统的压力控制提出一种具有良好自适应性的算法设计思路。

关键词: 电动助力制动系统, 液压力控制, RBF滑模, 快速原型

Abstract: To solve the problem of nonlinearity and inconsistency of hydraulic brake system in the pressure control of automobile electric booster(EBooster) braking system, a sliding mode variable structure control method based on radial based function(RBF) neural network is proposed. The pressure control architecture of EBooster is designed and a simplified equivalent structure model of hydraulic braking system is established. Then the hydraulic pressure sliding mode control method based on RBF network is designed. The sliding mode control parameters of the system are adaptively adjusted by designing the adaptive law of RBF network. The stability of the algorithm is analyzed by Lyapunov function. Finally, the rapid control prototyping(RCP) experiment platform of electric power-assisted brake system is built and the algorithm is verified by RCP test. The experimental results show that the control strategy of the sliding mode control method based on RBF network has a good performance with a control error no larger than 2%. A design method of adaptive pressure control algorithm is provided for the EBooster system.

Key words: electric power-assisted brake system, hydraulic pressure control, RBF based sliding mode control, rapid control prototyping (RCP)

中图分类号:

U463

赵健, 邓志辉, 朱冰, 常婷婷, 陈志成. 基于RBF网络滑模的电动助力制动系统液压力控制[J]. 机械工程学报, 2020, 56(24): 106-114.

ZHAO Jian, DENG Zhihui, ZHU Bing, CHANG Tingting, CHEN Zhicheng. Sliding Mode Control Based on RBF Network for Hydraulic Pressure in Electric Power-assisted Brake System[J]. Journal of Mechanical Engineering, 2020, 56(24): 106-114.

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基于RBF网络滑模的电动助力制动系统液压力控制

Sliding Mode Control Based on RBF Network for Hydraulic Pressure in Electric Power-assisted Brake System

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