NDLI: Robust Model Predictive Flight Control of Unmanned Rotorcrafts

Content Provider	Springer Nature Link
Author	Alexis, Kostas Papachristos, Christos Siegwart, Roland Tzes, Anthony
Copyright Year	2015
Abstract	This paper addresses the problem of robust flight control of unmanned rotorcrafts, by proposing and experimentally evaluating a real–time robust model predictive control scheme in various challenging conditions, aiming to capture the demanding nature of the potential requirements for their efficient and safe integration in real–life operations. The control derivation process is based on state space representations applicable in most rotorcraft configurations and incorporate the effects of external disturbances. Exploiting this modeling approach, two different unmanned rotorcraft configurations are presented and experimentally utilized. The formulated control strategy consists of a receding horizon scheme, the optimization process of which employs the minimum peak performance measure, while incorporating and accounting for the modeled dynamics and input and state constraints. This strategy aims to ensure the minimum possible deviation subject to the worst–case disturbance, while robustly respecting and satisfying the physical limitations of the system, or a set of mission-related requirements, as encoded in the constraints. The proposed framework is further augmented in order to provide obstacle avoidance capabilities into a unified scheme. Multiparametric methods were utilized in order to provide an explicit solution to the controller computation optimization problem, therefore allowing for fast real–time execution and seamless integration into any digital avionics system. The efficiency of the proposed strategy is validated via several experimental case studies on the two unmanned rotorcraft platforms. The experiments set consists of: trajectory tracking subject to atmospheric disturbances, slung load operations, fast highly disturbed maneuvers, collisions handling, as well as avoidance of known obstacles.
Starting Page	443
Ending Page	469
Page Count	27
File Format	PDF
ISSN	09210296
Journal	Journal of Intelligent & Robotic Systems
Volume Number	81
Issue Number	3-4
e-ISSN	15730409
Language	English
Publisher	Springer Netherlands
Publisher Date	2015-06-12
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	Unmanned aerial systems MPC Robust control 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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