Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre line. A force-input nonlinear bicycle vehicle model is developed and used in the RNMPC control design. A robust invariant set is used in the RNMPC design to guarantee that state and input constraints are satisfied in the presence of disturbances and model error. Simulations and experiments on a vehicle show the effectiveness of the proposed framework. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Vehicle System Dynamics Taylor & Francis

A tube-based robust nonlinear predictive control approach to semiautonomous ground vehicles

22 pages

Loading next page...
 
/lp/taylor-francis/a-tube-based-robust-nonlinear-predictive-control-approach-to-HB80nUUON9

References (27)

Publisher
Taylor & Francis
Copyright
© 2014 Taylor & Francis
ISSN
1744-5159
eISSN
0042-3114
DOI
10.1080/00423114.2014.902537
Publisher site
See Article on Publisher Site

Abstract

This paper proposes a robust control framework for lane-keeping and obstacle avoidance of semiautonomous ground vehicles. It presents a systematic way of enforcing robustness during the MPC design stage. A robust nonlinear model predictive controller (RNMPC) is used to help the driver navigating the vehicle in order to avoid obstacles and track the road centre line. A force-input nonlinear bicycle vehicle model is developed and used in the RNMPC control design. A robust invariant set is used in the RNMPC design to guarantee that state and input constraints are satisfied in the presence of disturbances and model error. Simulations and experiments on a vehicle show the effectiveness of the proposed framework.

Journal

Vehicle System DynamicsTaylor & Francis

Published: Jun 3, 2014

Keywords: vehicle safety; uncertain dynamics; robust control; active safety; autonomous vehicles; robust nonlinear MPC

There are no references for this article.