Paper Title :LPV-MPC Control and Self-Tuning Feedback Gains for the Trajectory Tracking of a Quadqopter UAV
Author :Jose A. Tolentino, Ricardo R. Rodriguez, Jose F. Oliden
Article Citation :Jose A. Tolentino ,Ricardo R. Rodriguez ,Jose F. Oliden ,
(2021 ) " LPV-MPC Control and Self-Tuning Feedback Gains for the Trajectory Tracking of a Quadqopter UAV " ,
International Journal of Mechanical and Production Engineering (IJMPE) ,
pp. 8-16,
Volume-9,Issue-7
Abstract : Reaching applications of artificial intelligence in control systems to autonomously drive unmanned aircraft is an
increasing area of interest in engineering. The purpose of this research is to investigate and apply machine learning along
with control systems algorithms to autonomously track the flight trajectory of anunmanned aerial vehicle (UAV) based on a
given path.In this sense, using a combination of Feedback Input State, Model Predictive Control (MPC) and Gradient
Descent, this study analyzes the capabilities to track the position and attitude of a UAV. Moreover, the use of gradient
descent to generate accurate feedback gains was found to play the greatest role in providing the UAV a better performance in
autonomous flight.Hence, this study definitively relates the use of fitted gains computed through machine learning and later
profited by the feedback controller. Further studies are needed to stablish thresholds in the control input, required in a real
prototype implementation.
Keywords - UAV, MIMO, MPC, Runge-Kutta, LPV, Feedback Input state, Machine Learning, Gradient Descent.
Type : Research paper
Published : Volume-9,Issue-7
DOIONLINE NO - IJMPE-IRAJ-DOIONLINE-18111
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Copyright: © Institute of Research and Journals
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Published on 2021-10-28 |
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