A model predictive speed tracking control approach for autonomous ground vehicles

被引：112

作者：

Zhu, Min ^{[1
]}

Chen, Huiyan ^{[1
]}

Xiong, Guangming ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Mech Engn, Beijing, Peoples R China

来源：

MECHANICAL SYSTEMS AND SIGNAL PROCESSING | 2017年 / 87卷

基金：

中国国家自然科学基金;

关键词：

Speed tracking; Speed control; Autonomous ground vehicles; Model predictive control; Real-time optimization; CONTROL DESIGN; THROTTLE;

D O I：

10.1016/j.ymssp.2016.03.003

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper presents a novel speed tracking control approach based on a model predictive control (MPC) framework for autonomous ground vehicles. A switching algorithm without calibration is proposed to determine the drive or brake control. Combined with a simple inverse longitudinal vehicle model and adaptive regulation of MPC, this algorithm can make use of the engine brake torque for various driving conditions and avoid high frequency oscillations automatically. A simplified quadratic program (QP) solving algorithm is used to reduce the computational time, and the approach has been applied in a 16-bit microcontroller. The performance of the proposed approach is evaluated via simulations and vehicle tests, which were carried out in a range of speed-profile tracking tasks. With a well-designed system structure, high-precision speed control is achieved. The system can robustly model uncertainty and external disturbances, and yields a faster response with less overshoot than a PI controller. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：138 / 152

页数：15

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