Trajectory Tracking for Unmanned Vehicle Based on Model Predictive Control Using Linear Matrix Inequalities

被引：2

作者：

Lei, Zhiling ^{[1
]}

Tang, Xiaoming ^{[1
]}

机构：

[1] Chongqing Univ Posts & Telecommun, Coll Automat, Chongqing, Peoples R China

来源：

2020 CHINESE AUTOMATION CONGRESS (CAC 2020) | 2020年

关键词：

trajectory tracking; model predictive control(MPC); unmanned vehicle;

D O I：

10.1109/CAC51589.2020.9327228

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper researches the problem of trajectory tracking of the unmanned vehicle on the basis of the Model Predictive Control (MPC) approach. The dynamic behavior of the unmanned vehicle system is predicted by establishing a linear tracking error model. The model predictive controller is addressed through an infinite horizon optimization problem which specifically considers the constraints on the rear axle center speed and the deflection angle of front wheel of the vehicle. The overall MPC optimization problem is converted into a convex optimization problem, which is dealt with by the Linear Matrix Inequality (LMI) technique. The effectiveness of the provided strategy is verified by the co-simulation platform of MATLAB and Carsim.

引用

页码：698 / 703

页数：6

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