NDLI: An Efficient Model Predictive Control Scheme for an Unmanned Quadrotor Helicopter

Content Provider	Springer Nature Link
Author	Abdolhosseini, M. Zhang, Y. M. Rabbath, C. A.
Copyright Year	2012
Abstract	In this paper, an efficient Model Predictive Control (eMPC) algorithm deploying fewer prediction points and less computational requirement is presented in order to control a small or miniature unmanned quadrotor helicopter. A model reduction technique associated with the dynamics of an unmanned quadrotor helicopter is also put forward so as to minimize the burden of calculations in application of MPC into an airborne platform. For three-dimensional tracking control of the quadrotor helicopter, simulation results corresponding to the algebraic formulation—presented in this paper—versus the standard MPC formulation commonly found in the literature further illustrate effectiveness of this study. Unsuccessful implementation of the standard formulation on the testbed due to computational burden proves the necessity and advantages of this new approach. Eventually, to demonstrate effectiveness of the developed MPC algorithm, the suggested algebraic-based MPC framework is successfully implemented on an unmanned quadrotor helicopter testbed (known as Qball-X4) available at the Networked Autonomous Vehicles Lab (NAVL) of Concordia University for tracking control of the unmanned aerial vehicle.
Starting Page	27
Ending Page	38
Page Count	12
File Format	PDF
ISSN	09210296
Journal	Journal of Intelligent & Robotic Systems
Volume Number	70
Issue Number	1-4
e-ISSN	15730409
Language	English
Publisher	Springer Netherlands
Publisher Date	2012-08-02
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Model Predictive Control (MPC) Unmanned quadrotor helicopter Experimental flight test Control, Robotics, Mechatronics Electrical Engineering Artificial Intelligence (incl. Robotics) Mechanical Engineering
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software

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