The full text of this article


NMPC and genetic algorithm-based approach for trajectory tracking and collision avoidance of UAVs
by Luca De Filippis; Giorgio Guglieri
International Journal of Innovative Computing and Applications (IJICA), Vol. 5, No. 3, 2013


Abstract: Research on unmanned aircraft is improving constantly the autonomous flight capabilities of these vehicles in order to provide performance needed to employ them in even more complex tasks. UAV path planning (PP) system plans the best path to perform the mission and then it uploads this path on the flight management system (FMS) providing reference to the aircraft navigation. Tracking the path is the way to link kinematic references related to the desired aircraft positions with its dynamic behaviours, to generate the right command sequence. This paper presents a non-linear model predictive control (NMPC) system that tracks the reference path provided by PP and exploits a spherical camera model to avoid unpredicted obstacles along the path. The control system solves online (i.e., at each sampling time) a finite horizon (state horizon) open loop optimal control problem with a genetic algorithm. This algorithm finds the command sequence that minimises the tracking error with respect to the reference path, driving the aircraft far from sensed obstacles and towards the desired trajectory.

Online publication date: Fri, 16-Aug-2013


is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Innovative Computing and Applications (IJICA):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email