On the suitability of Nonlinear Model Predictive Control for Unmanned Ground Vehicles. Berkemeier, M. D., Perez, S., & Bevly, D. In 2014 American Control Conference, pages 4605–4610, June, 2014. ISSN: 2378-5861
Paper doi abstract bibtex Nonlinear Model Predictive Control (NMPC) has great appeal for vehicle path control due to its ability to easily handle nonlinear dynamic models with constraints while achieving near-optimal control. The drawback is that a straight-forward application results in computations that take too long for real-time use. In this paper, we explore these issues in the use of NMPC for vehicle control. Methods for speeding up the computations are discussed.
@inproceedings{berkemeier_suitability_2014,
title = {On the suitability of {Nonlinear} {Model} {Predictive} {Control} for {Unmanned} {Ground} {Vehicles}},
url = {https://ieeexplore.ieee.org/abstract/document/6858827},
doi = {10.1109/ACC.2014.6858827},
abstract = {Nonlinear Model Predictive Control (NMPC) has great appeal for vehicle path control due to its ability to easily handle nonlinear dynamic models with constraints while achieving near-optimal control. The drawback is that a straight-forward application results in computations that take too long for real-time use. In this paper, we explore these issues in the use of NMPC for vehicle control. Methods for speeding up the computations are discussed.},
urldate = {2024-06-20},
booktitle = {2014 {American} {Control} {Conference}},
author = {Berkemeier, Matthew D. and Perez, Sostenes and Bevly, David},
month = jun,
year = {2014},
note = {ISSN: 2378-5861},
keywords = {Automotive, Cost function, Mathematical model, Portable computers, Predictive control, Predictive control for nonlinear systems, Trajectory, Vehicles},
pages = {4605--4610},
}
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