contributor author | Zhou | |
contributor author | Xingyu;Wang | |
contributor author | Zejiang;Shen | |
contributor author | Heran;Wang | |
contributor author | Junmin | |
date accessioned | 2022-08-18T12:55:01Z | |
date available | 2022-08-18T12:55:01Z | |
date copyright | 4/28/2022 12:00:00 AM | |
date issued | 2022 | |
identifier issn | 0022-0434 | |
identifier other | ds_144_07_071007.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4287095 | |
description abstract | Driver's steering torque is an essential signal for automated and assistance driving systems to interpret the human driver's intention. In a steer-by-wire (SBW) apparatus, due to the inevitable couplings between the driver steering, electrical motor, and viscous frictional torques, such a vital signal cannot be directly measured via a torque transducer. Instead, model-based estimators are considered a more practicable route. Toward this end, this paper introduces a novel mixed L1/H2 observer to achieve a robust estimation respecting the human driver's steering torque in human-alone and human-automation shared driving. On the one hand, the L1 induced norm from the process disturbance to the estimation error is attenuated. On the other hand, the H2 synthesis seeks to suppress the effects of measurement noises from the steering angle encoder and the motor's current sensor. Driving simulator human subject experiments are effectuated to justify the proposed strategy and manifest its superiorities over a benchmark method. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | A Mixed L1/H2 Robust Observer With An Application To Driver Steering Torque Estimation for Autopilot-Human Shared Steering | |
type | Journal Paper | |
journal volume | 144 | |
journal issue | 7 | |
journal title | Journal of Dynamic Systems, Measurement, and Control | |
identifier doi | 10.1115/1.4054262 | |
journal fristpage | 71007-1 | |
journal lastpage | 71007-11 | |
page | 11 | |
tree | Journal of Dynamic Systems, Measurement, and Control:;2022:;volume( 144 ):;issue: 007 | |
contenttype | Fulltext | |