طراحی جرم کنترل موقعیت ماهواره مخابراتی زمین آهنگ با استفاده از داده‌کاوی

معانی, احسان; نیک پی, پیمان; ذبیحیان, احسان

doi:10.22034/jsst.2021.1221

نوع مقاله : مقالة‌ تحقیقی‌ (پژوهشی‌)

نویسندگان

¹ دانشیار، مهندسی مکانیک، دانشکده فنی، دانشگاه تهران، تهران، ایران.

² پژوهشکده سامانه‌های ماهواره، پژوهشگاه فضایی ایران، تهران، ایران

³ پژوهشکده سامانه های ماهواره، پژوهشگاه فضایی ایران، تهران، ایران

https://doi.org/10.22034/jsst.2021.1221

چکیده

در ماهواره‌های مخابراتی زمین آهنگ برای انجام ماموریت‌های از تراستر استفاده شده و نیاز به سوخت مصرفی می‌باشد. در این مقاله بر اساس یک روش جدید و بدون نیاز به روابط ریاضی حاکم بر دینامیک ماهواره و تنها بر اساس داده‌های موجود برای ماهواره‌های پیشین به تعیین جرم سوخت ماهواره‌های مخابراتی پرداخته می‌شود. برای این منظور از روش حداقل مربعات خطا و شبکه عصبی مصنوعی استفاده شده و دو روش از نظر دقت مقایسه شده و دو مدل ریاضی برای تشخیص جرم سوخت ماهواره بر اساس پارامترهای طراحی آن ارائه شده است. با مقایسه خروجی مدل برای چندین ماهواره واقعی و مقایسه با جرم سوخت واقعی آن‌ها مشخص شد که روابط ارائه شده دارای دقت بالای 95 درصد است و برای امکان‌سنجی و طراحی مفهومی پروژه‌های ماهواره بسیار مناسب و کارا می‌باشند. هم‌چنین برای مدل خطی به دست آمده تحلیل حساسیت انجام شده و در نهایت روش ارائه شده برای به محاسبه حجم ماهواره نیز مورد ارزیابی قرار گرفته است

کلیدواژه‌ها

20.1001.1.20084560.1400.14.1.3.0

عنوان مقاله [English]

GEO satellite station keeping mass design based on data mining

نویسندگان [English]

Ehsan Maani ¹
Peyman Nikpey ²
Ehsan Zabihian ³

¹ Associate Professor, Department of Mechanical Engineering, University of Tehran, Tehran, Iran.

² Satellite Research Institute, Iranian Research Center, Tehran, Iran

³ Satellite Research Institute, Iranian Research Center, Tehran, Iran

چکیده [English]

n GEO communicational satellites, thrusts are being used for many missions such as station keeping, longitude change maneuver and actuators desaturation. These types of actuators need fuel and its estimation requires many complicated calculations. In this paper, a novel method based on availed data for previous satellites is proposed for estimation of satellite fuel mass and it does not need mathematical modeling of satellite dynamics. Two methods, least square method and artificial intelligence, are used to this aim and two mathematical model are proposed for satellite fuel mass estimation. By applying the models to several previous satellites, it is shown that the models have lower than 5% average error. The proposed method in this paper is quick and accurate and can be utilized for GEO satellites feasibility study and conceptual design

کلیدواژه‌ها [English]

GEO satellite
Fuel mass
Neural networks
Artificial intelligence
Data mining

مراجع

[1] Shrivastava, S.K., "Orbital Perturbations and Stationkeeping of Communication Satellites," Journal of Spacecraft and Rockets, Vol. 15, No. 2, 1978, pp. 67-78.

[2] Circi, C., "Simple Strategy for Geostationary Stationkeeping Maneuvers Using Solar Sail," Journal of Guidance, Control, and Dynamics,. Vol. 28, No. 2, 2005, pp. 249-253.

[3] Borissov, S., Wu, Y. and Mortari, D., "East–West GEO Satellite Station-Keeping with Degraded Thruster Response," Aerospace, Vol. 2, No. 4, pp. 581-601.

[4] Gomes, V.M. and Prado, A.F., "Low-thrust out-of-Plane Orbital Station-keeping Maneuvers for Satellites," Mathematical Problems in Engineering, Vol. 2012, 2012, p. 14.

[5] Sukhanov, A. and Prado, A., "On One Approach to the Optimization of Low-thrust Station Keeping Manoeuvres." Advances in Space Research,. Vol. 50, No. 11, 2012, pp. 1478-1488.

[6] Yang, W. and Li, S., "A Station-keeping Control Method for GEO Spacecraft Based on Autonomous Control Architecture," Aerospace Science and Technology, Vol. 45: 2015, pp. 462-475.

[7] Gazzino, C. and et al., "Optimal Control for Minimum-fuel Geostationary Station Keeping of Satellites Equipped with Electric Propulsion". IFAC-PapersOnLine, Vol. 49, No. 17, 2016, pp. 379-384.

[8] Arvelo, E.R. and Martins, N.C., "Optimal Sensor Scheduling for Station-keeping in Denied Environments", Journal of the Franklin Institute, Vol. 356, Issue 17, 2019, pp. 10480-10513.

[9] Weiss, A., Kalabić, U.V. and Di, S., Cairano, "Station keeping and momentum management of low-thrust satellites using MPC." Aerospace Science and Technology, Vol. 76, 2018, pp. 229-241.

[10] de Almeida Prado, A.F.B., "Searching for orbits with minimum fuel consumption for station-keeping maneuvers: an application to lunisolar perturbations." Mathematical Problems in Engineering, Vol. 2013, 2013, p. 11.

[11] Losa, D. and et al., "Electric Station Keeping of Geostationary Satellites: A Differential Inclusion Approach," in Proceedings of the 44^th IEEE Conference on Decision and Control (IEEE), 2005.

[12] Li, L. and et al., "Geostationary Station-Keeping With Electric Propulsion in Full and Failure Modes." Acta Astronautica, Vol. 163, part 2, 2019, pp. 130-144.

[13] Braha, D., Data Mining for Design and Manufacturing: Methods and Applications, Vol. 3, Springer Science & Business Media, 2013.

[14] Brown, D.C., Artificial Intelligence for Design Process Improvement, in Design Process Improvement, Springer. 2005, p. 158-173.

[15] Tavakoli, M. and N. Assadian, "Predictive Fault-Tolerant Control of an All-Thruster Satellite In 6-DOF Motion Via Neural Network Model Updating," Advances in Space Research, Vol. 61, No. 6, 2018, pp. 1588-1599.

[16] Baldi, P., et al., "Combined Geometric And Neural Network Approach to Generic Fault Diagnosis in Satellite Actuators and Sensors," IFAC-Papers On Line, Vol. 49, 17, 2016, pp. 432-437.

[17] Zhu, Q. and et al., "U-Neural Network-Enhanced Control of Nonlinear Dynamic Systems," Neurocomputing, Vol. 352, 2019, pp. 12-21.

[18] Shamlu, F. and Naghash, A. "Satellite Orbit Prediction Through Observation Data and the Artificial Neural Networks", Journal of Space Science and Technology (JSST), Vol. 10, No. 2, 2017. pp. 1-8.

[19] Emme, E.M., A History of Space Flight. Vol. 27. Holt McDougal, 1965.

[20] edited By: Wertz, J.R., Everett, D.F. and Puschell, J.J., Space Mission Engineering: The New SMAD2011: Microcosm Press.

[21] Wertz, J.R. and Larson, W.J. Space Mission Analysis and Design, Edition 3., Space Technology Library, 1992.

[22] Fortescue, P., Swinerd, G. and Stark, J., Spacecraft Systems Engineering, John Wiley & Sons, 2011.

[23] Brown, C.D., Elements of spacecraft design 2002: Aiaa.

[24] Mirshams, M., Saghari, A. and Zabihian, E., "Complementary Method the Conceptual Design of Space Craft Electrical Power Subsystem," Journal of Space Science and Technology (JSST), Vol. 8, No. 3, 2015, pp. 55-63.

[25] Riaz, R. and et al., "Using Statistical and Artificial Intelligence Approach to Predict The Exhaust Gas Temperature of A Micro Gas Turbine Engine," Aerospace Knowledge and Technology Journal, Vol. 4, No. 2, 2015, pp. 77-94.

[26] Zabihian, E., Novel Method for GEO Satelittes Conceptual Design, (Thesis PhD) KNT University, Iran, 2018.

[27] Ljung, L., System Identification. Wiley Encyclopedia of Electrical and Electronics Engineering, 1999و, p. 1-19.

[28] Karlik, B. and Olgac, A.V., "Performance Analysis of Various Activation Functions In Generalized MLP Architectures of Neural Networks." International Journal of Artificial Intelligence and Expert Systems, Vol. 1, No. 4, 2011, pp. 111-122.

[29] Shanmuganathan, S., Artificial Neural Network Modelling: An Introduction, In Artificial Neural Network Modelling, Springer,2016, pp. 1-14.

علوم و فناوری فضایی

طراحی جرم کنترل موقعیت ماهواره مخابراتی زمین آهنگ با استفاده از داده‌کاوی

مراجع

مراجع

دوره 14، شماره 1 - شماره پیاپی 46
فروردین 1400
صفحه 23-33

طراحی جرم کنترل موقعیت ماهواره مخابراتی زمین آهنگ با استفاده از داده‌کاوی

مراجع

مراجع

دوره 14، شماره 1 - شماره پیاپی 46فروردین 1400صفحه 23-33

دوره 14، شماره 1 - شماره پیاپی 46
فروردین 1400
صفحه 23-33