Title: Learning in Centralized Nonlinear Model Predictive Control: Application to an Autonomous Tractor-Trailer System
Authors: Kayacan, Erkan ×
Kayacan, Erdal
Ramon, Herman
Saeys, Wouter #
Issue Date: Jan-2015
Publisher: Institute of Electrical and Electronics Engineers
Series Title: IEEE Transactions on Control Systems Technology vol:23 issue:1 pages:197-205
Abstract: One of the most critical tasks in tractor operation is the accurate steering during field operations, e.g., accurate trajectory following during mechanical weeding or spraying, to avoid damaging the crop or planting when there is no crop yet. To automate the trajectory following problem of an autonomous tractor-trailer system and also increase its steering accuracy, a nonlinear model predictive control approach has been proposed in this paper. For the state and parameter estimation, moving horizon estimation has been chosen since it considers the state and the parameter estimation within the same problem and also constraints both on inputs and states can be incorporated. The experimental results show the accuracy and the efficiency of the proposed control scheme in which the mean values of the Euclidean error for the tractor and the trailer, respectively, are 6.44 and 3.61 cm for a straight line trajectory and 49.78 and 41.52 cm for a curved line trajectory.
ISSN: 1063-6536
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Mechatronics, Biostatistics and Sensors (MeBioS)
× corresponding author
# (joint) last author

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