Paper Info
Title
Driver-Behavior-Based Adaptive Steering Robust Nonlinear Control of Unmanned Driving Robotic Vehicle With Modeling Uncertainties and Disturbance Observer
Abstract
In this paper, an adaptive steering robust nonlinear control method based on driver behavior is presented for an unmanned driving robotic vehicle (UDRV), in order to achieve accurate and stable steering control of UDRV. Considering modeling uncertainties and unknown nonlinear external disturbances, a UDRV nonlinear dynamics model is established. A driver behavior model is established considering a coordinate transformation model, a driver virtual path planning model, and a driver desired yaw rate model. On the basis of this, an adaptive steering robust nonlinear controller for UDRV is presented, consisting of an adaptive robust backstepping controller and a nonlinear disturbance observer (NDO). The NDO is designed to compensate for modeling uncertainties and unknown nonlinear external disturbances. The adaptive steering robust nonlinear controller for UDRV is designed through backstepping method and NDO compensation. The stability of control system is proved. Finally, double lane change experiments are conducted. Comparison analysis results among the proposed control method, other existed control method, and human driver demonstrate the effectiveness of the proposed method.
Year
DOI
Venue
2019
10.1109/TVT.2019.2922452
IEEE Transactions on Vehicular Technology
Keywords
Field
DocType
Vehicles,Adaptation models,Uncertainty,Wheels,Robot kinematics,Tires
Motion planning,Backstepping,Control theory,Nonlinear system,Control theory,Computer science,Nonlinear control,Electronic engineering,Control system,Observer (quantum physics),Yaw
Journal
Volume
Issue
ISSN
68
8
0018-9545
Citations 
PageRank 
References 
1
0.36
0
Authors
5
Name
Order
Citations
PageRank
Gang Chen152.19
Shoubao Chen210.36
Reza Langari315035.75
Xu Li410.36
Wei-gong Zhang541.41