کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4976912 1451837 2018 22 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Model predictive and reallocation problem for CubeSat fault recovery and attitude control
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Model predictive and reallocation problem for CubeSat fault recovery and attitude control
چکیده انگلیسی


- Innovative fault-tolerant algorithm for attitude control with magnetic torquers.
- Model Predictive Control applied to a CubeSat mission.
- Autonomous fault recovery without hot or cold redundancies.
- Algorithm is adaptable from CubeSat to flagship missions.

In recent years, thanks to the increase of the know-how on machine-learning techniques and the advance of the computational capabilities of on-board processing, expensive computing algorithms, such as Model Predictive Control, have begun to spread in space applications even on small on-board processor. The paper presents an algorithm for an optimal fault recovery of a 3U CubeSat, developed in MathWorks Matlab & Simulink environment. This algorithm involves optimization techniques aiming at obtaining the optimal recovery solution, and involves a Model Predictive Control approach for the attitude control. The simulated system is a CubeSat in Low Earth Orbit: the attitude control is performed with three magnetic torquers and a single reaction wheel. The simulation neglects the errors in the attitude determination of the satellite, and focuses on the recovery approach and control method. The optimal recovery approach takes advantage of the properties of magnetic actuation, which gives the possibility of the redistribution of the control action when a fault occurs on a single magnetic torquer, even in absence of redundant actuators. In addition, the paper presents the results of the implementation of Model Predictive approach to control the attitude of the satellite.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanical Systems and Signal Processing - Volume 98, 1 January 2018, Pages 1034-1055
نویسندگان
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