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Implementation and Analysis of a Model Predictive Controller for Landing Fixed-Wing Aircraft on Mobile Platforms

Fracaroli Pavani, Marcus Felipe (2018) Implementation and Analysis of a Model Predictive Controller for Landing Fixed-Wing Aircraft on Mobile Platforms. DLR-Interner Bericht. DLR-IB-RM-OP-2018-78. Master's. TU München. 102 S.

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High-Altitude Long Endurance (HALE) aircraft have become an intriguing Topic of interest, since these vehicles are capable of staying aloft in the stratosphere for Long periods of time. However, a major issue with these aircraft is the inherent lightweight design, which leads to fragile structures with low payload capacities. Muskardin et al. [1] have proposed a novel landing system to increase the capabilities of such aircraft: to remove the landing gear and land instead on a platform mounted on top of a ground vehicle. The system proposed in [1] was validated through several successful landing experiments, but the developed architecture was not optimal. In the presence of disturbances, it often necessary to abort and retry the maneuver, which is a problem, since only a few retries are possible before the experiment has to be restarted completely. With this in mind, Persson et al. [2] developed a Model Predictive Controller (MPC) for this maneuver, where landing time and some of the terminal states are kept free to increase the flexibility of the solution, while safety guarantees are indirectly provided by the controller through optimization constraints. This project aims at the implementation and analysis of the MPC developed in [2]. The goal of this project is to achieve a smooth and continuous landing in the presence of disturbances, while adding maneuver shaping capabilities through optimization. Therefore, our main objectives are the implementation of the MPC in MATLAB/Simulink® ; the formulation of landing requirements; the implementation of adaptive limits (with the help of a pseudo-wind estimate), adaptive weights and runway prediction; and the validation of the architecture through testing with various disturbances. The choice of individual weights that compose the various weighting matrices presented in this work have proven to have a big influence on the system’s performance. The implementation of adaptive limits was also proven very useful, as it led to successful landings in cases of head-, tail- and crosswind. Furthermore, the results obtained after the implementation of adaptive weights were very positive, as this modification led to successful landings in cases of up- and downdrafts as well. The final simulated architecture has shown a respectable performance and is able to compensate for horizontal wind gusts of up to 5 m/s, thus meeting the Project requirements. The best performance was shown in the cases of crosswind, as the MPC was able to compensate for winds of up to 12.5 m/s, which is very promising for this type of light-weight aircraft, since conventional landings in such conditions require a risky de-crab maneuver right before touchdown.

Item URL in elib:https://elib.dlr.de/120003/
Document Type:Monograph (DLR-Interner Bericht, Master's)
Title:Implementation and Analysis of a Model Predictive Controller for Landing Fixed-Wing Aircraft on Mobile Platforms
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Number of Pages:102
Keywords:Model Predictive Control, Fixed-Wing Aircraft, Landing on Mobile Platforms
Institution:TU München
Department:Fakultät für Maschinenwesen
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Terrestrial Assistance Robotics (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Analysis and Control of Advanced Robotic Systems
Deposited By: Muskardin, Tin
Deposited On:18 May 2018 03:43
Last Modified:18 May 2018 03:43

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