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Hierarchical Predictive Control for Ground-Vehicle Maneuvering

Berntorp, Karl and Magnusson, Fredrik LU (2015) American Control Conference, 2015 In Proceedings of the 2015 American Control Conference p.2771-2776
Abstract
This paper presents a hierarchical approach to feedback-based trajectory generation for improved vehicle autonomy. Hierarchical vehicle-control structures have been used before—for example, in electronic stability control systems, where a low-level control loop tracks high-level references. Here, the control structure includes a nonlinear vehicle model already at the high level to generate optimization-based references. A nonlinear model-predictive control (MPC) formulation, combined with a linearized MPC acting as a backup controller, tracks these references by allocating torque and steer commands. With this structure the two control layers have a physical coupling, which makes it easier for the low-level loop to track the references.... (More)
This paper presents a hierarchical approach to feedback-based trajectory generation for improved vehicle autonomy. Hierarchical vehicle-control structures have been used before—for example, in electronic stability control systems, where a low-level control loop tracks high-level references. Here, the control structure includes a nonlinear vehicle model already at the high level to generate optimization-based references. A nonlinear model-predictive control (MPC) formulation, combined with a linearized MPC acting as a backup controller, tracks these references by allocating torque and steer commands. With this structure the two control layers have a physical coupling, which makes it easier for the low-level loop to track the references. Simulation results show improved performance over an approach based on linearized MPC, as well as feasibility for online implementations. (Less)
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author
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Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
Proceedings of the 2015 American Control Conference
pages
2771 - 2776
conference name
American Control Conference, 2015
external identifiers
  • scopus:84940902577
project
collocation
LCCC
language
English
LU publication?
yes
id
24870a96-55f6-497b-95cb-2a73179db251 (old id 5031551)
date added to LUP
2015-02-03 17:39:15
date last changed
2017-03-05 04:33:56
@inproceedings{24870a96-55f6-497b-95cb-2a73179db251,
  abstract     = {This paper presents a hierarchical approach to feedback-based trajectory generation for improved vehicle autonomy. Hierarchical vehicle-control structures have been used before—for example, in electronic stability control systems, where a low-level control loop tracks high-level references. Here, the control structure includes a nonlinear vehicle model already at the high level to generate optimization-based references. A nonlinear model-predictive control (MPC) formulation, combined with a linearized MPC acting as a backup controller, tracks these references by allocating torque and steer commands. With this structure the two control layers have a physical coupling, which makes it easier for the low-level loop to track the references. Simulation results show improved performance over an approach based on linearized MPC, as well as feasibility for online implementations.},
  author       = {Berntorp, Karl and Magnusson, Fredrik},
  booktitle    = {Proceedings of the 2015 American Control Conference},
  language     = {eng},
  pages        = {2771--2776},
  title        = {Hierarchical Predictive Control for Ground-Vehicle Maneuvering},
  year         = {2015},
}