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Attitude Determination and Control of Thinsat System Using Adaptive Control Technique

Received: 20 March 2023     Accepted: 20 April 2023     Published: 10 June 2023
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Abstract

This paper presents attitude determination and control of ThinSat system using an adaptive control technique. This study aims to reduce the impact of dynamic torque on the angular velocity and orientation of spacecraft while maintaining a steady position in the axes. This was achieved by collecting the data of Nigeria Sat-2 which was trained with a multi-layered neural network algorithm employed to generate an adaptive control system which was implemented on the satellite using Simulink software. The training performance of the adaptive controller was evaluated and validated using Mean Square Error (MSE) and regression. The result showed that the average MSE is 0045394Mu and 0.97271 for regression. The implication is that the neural network correctly learns the spacecraft data collected and was able to detect changes in the angular velocity. The step response of the adaptive controller was evaluated with the characterized Proportional Integral Derivative (PID) control system and the result showed that the total time of the attitude determination and control of the spacecraft is 111.24ms as against 465ms with PID which gives 76% reduction in decision time to control error due to dynamics. The comparative analysis with the characterized in the rate of error minimization on the pitch angular velocity showed that the angle was reduced from 13.46mm with the adaptive controller to 9.55mm which gives a percentage improvement of 29%.

Published in Engineering Science (Volume 8, Issue 2)
DOI 10.11648/j.es.20230802.11
Page(s) 14-22
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

ThinSat, Adaptive Control, Spacecraft, Nigeria Sat-2, Neural Network

References
[1] Alexandre C., David V., Jaume J., Enric J., Roger O., Adrià A., Joan F., Pol V., &Adriano C., (2016). 3CAT-2: Attitude Determination and Control System for a GNSS-R Earth Observation 6U CubeSat Mission, European Journal of Remote Sensing, 49: 1, 759-776, DOI: 10.5721/EuJRS20164940.
[2] Assaad F., Jighjigh I., Ye L., Alan S., (2014). Attitude Determination and Control System. Bachelor of Science Project. (Accessed on July 12th 2022).
[3] Bak T. (1999). Spacecraft Attitude Determination - a Magnetometer Approach, Ph.D. Thesis, Aalborg University. (Accessed on July 15th 2022).
[4] Barsukow W., Edelmann P., Klingenberg C., Ropke F., (2017). A low-Mach Roe-type solver for the Euler equations allowing for gravity source terms. ESAIM Proceedings and Surveys 58: 27-39 DOI: 10.1051/proc/201758027.
[5] Carlo N., (2020). In-orbit data-driven parameter estimation for attitude control of satellites. Automatic. Université de Lorraine. English. ffNNT: 2020LORR0058ff. fftel-02949320f.
[6] Chen Z., Li C., Sanchez R., (2015). 1684. Multi-layer Neural Network with Deep Belief Network for Gearbox Fault Diagnosis. © JVE International Ltd. Journal of Vibroengineering. AUG 2015, VOLUME 17, ISSUE 5. ISSN 1392-8716 https://core.ac.uk/display/323314109?utm_source=pdf&utm_medium=banner&utm_campaign=pdf-decoration-v1
[7] Christopher D., (2003), Spacecraft Attitude Dynamics and Control, chapter 4. http://www.aoe.vt.edu/~cdhall/courses/aoe4140/attde.pdf. (Accessed on July 15th 2022).
[8] Cullen M., (2016). Guidance, Navigation, And Control of Small Satellite Attitude Using Micro-Thrusters. A Dissertation Submitted To The Graduate Division Of The University Of Hawai‘I At Manoa Master of Science Dessertation In Mechanical Engineering. (Accessed on July 13th 2022).
[9] Espen O., (2018) “Modelling and attitude control of elliptical orbits; applied modern control” DOI: 10.5772/intechopen.80422; available at https://www.intechopen.com/chapters/63931
[10] Sakai S., Fukushima Y., Saito H., (2008). Design and on-orbit evaluation of magnetic attitude control system for the “REIMEI” microsatellite, Advanced motion Control, 2008. AMC '08. 10th IEEE International Workshop on, pp. 584-589, 26-28 March 2008.
[11] Samuel O., (2015). Nigerian Communication Satellite and the Quest for Sustainable National development, American Journal of Social Science Research, 1 (1), 2015, 1-8. Retrieved from: http://www.publicscienceframework.org/journal/ajssr
[12] Yuri V. Kim (2020). Satellite Control System: Part I - Architecture and Main Components DOI: http://dx.doi.org/10.5772/intechopen.92575
[13] Virgili-Llop J, Polat H. and Romano M (2019) Attitude Stabilization of Spacecraft in Very Low Earth Orbit by Center-Of-Mass Shifting. Front. Robot. AI 6: 7. doi: 10.3389/frobt.2019.00007.
[14] Tam N., Kerri C., and Anne M., (2018). Attitude Determination for Small Satellites with Infrared Earth Horizon Sensors. JOURNAL OF SPACECRAFT AND ROCKETS Vol. 55, No. 6, November–December 2018. Downloaded by 129.205.112.63 on March 3, 2021 | http://arc.aiaa.org | DOI: 10.2514/1.A34010.
[15] Reyhanoglu M., Drakunov S. (2018) - Attitude Stabilization of Small Satellites Using Only Magnetic Actuation. Proceedings of IEEE Industrial Electronics Society, pp. 103-107. doi: http://dx.doi.org/10.1109/iecon.2008.4757936.
[16] John C. (2018). Satellite Attitude Determination with Low-Cost Sensors. Ph.D. Thesis, Aerospace Engineering in the University of Michigan. (Accessed on July 15th 2022).
[17] Klaus S., (2018). Mission Analyses for Low-Earth-Observation Missions with Spacecraft Formations. Chair Robotics and Telematics Julius-Maximilians-University Würzburg Am Hubland D-97074 Würzburg GERMANY. RTO-EN-SCI-231
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  • APA Style

    Ukonu Ihuoma Christian, Eneh Innocent Ifeanyichukwu, Ene Princewill Chigozie. (2023). Attitude Determination and Control of Thinsat System Using Adaptive Control Technique. Engineering Science, 8(2), 14-22. https://doi.org/10.11648/j.es.20230802.11

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    ACS Style

    Ukonu Ihuoma Christian; Eneh Innocent Ifeanyichukwu; Ene Princewill Chigozie. Attitude Determination and Control of Thinsat System Using Adaptive Control Technique. Eng. Sci. 2023, 8(2), 14-22. doi: 10.11648/j.es.20230802.11

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    AMA Style

    Ukonu Ihuoma Christian, Eneh Innocent Ifeanyichukwu, Ene Princewill Chigozie. Attitude Determination and Control of Thinsat System Using Adaptive Control Technique. Eng Sci. 2023;8(2):14-22. doi: 10.11648/j.es.20230802.11

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  • @article{10.11648/j.es.20230802.11,
      author = {Ukonu Ihuoma Christian and Eneh Innocent Ifeanyichukwu and Ene Princewill Chigozie},
      title = {Attitude Determination and Control of Thinsat System Using Adaptive Control Technique},
      journal = {Engineering Science},
      volume = {8},
      number = {2},
      pages = {14-22},
      doi = {10.11648/j.es.20230802.11},
      url = {https://doi.org/10.11648/j.es.20230802.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.es.20230802.11},
      abstract = {This paper presents attitude determination and control of ThinSat system using an adaptive control technique. This study aims to reduce the impact of dynamic torque on the angular velocity and orientation of spacecraft while maintaining a steady position in the axes. This was achieved by collecting the data of Nigeria Sat-2 which was trained with a multi-layered neural network algorithm employed to generate an adaptive control system which was implemented on the satellite using Simulink software. The training performance of the adaptive controller was evaluated and validated using Mean Square Error (MSE) and regression. The result showed that the average MSE is 0045394Mu and 0.97271 for regression. The implication is that the neural network correctly learns the spacecraft data collected and was able to detect changes in the angular velocity. The step response of the adaptive controller was evaluated with the characterized Proportional Integral Derivative (PID) control system and the result showed that the total time of the attitude determination and control of the spacecraft is 111.24ms as against 465ms with PID which gives 76% reduction in decision time to control error due to dynamics. The comparative analysis with the characterized in the rate of error minimization on the pitch angular velocity showed that the angle was reduced from 13.46mm with the adaptive controller to 9.55mm which gives a percentage improvement of 29%.},
     year = {2023}
    }
    

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  • TY  - JOUR
    T1  - Attitude Determination and Control of Thinsat System Using Adaptive Control Technique
    AU  - Ukonu Ihuoma Christian
    AU  - Eneh Innocent Ifeanyichukwu
    AU  - Ene Princewill Chigozie
    Y1  - 2023/06/10
    PY  - 2023
    N1  - https://doi.org/10.11648/j.es.20230802.11
    DO  - 10.11648/j.es.20230802.11
    T2  - Engineering Science
    JF  - Engineering Science
    JO  - Engineering Science
    SP  - 14
    EP  - 22
    PB  - Science Publishing Group
    SN  - 2578-9279
    UR  - https://doi.org/10.11648/j.es.20230802.11
    AB  - This paper presents attitude determination and control of ThinSat system using an adaptive control technique. This study aims to reduce the impact of dynamic torque on the angular velocity and orientation of spacecraft while maintaining a steady position in the axes. This was achieved by collecting the data of Nigeria Sat-2 which was trained with a multi-layered neural network algorithm employed to generate an adaptive control system which was implemented on the satellite using Simulink software. The training performance of the adaptive controller was evaluated and validated using Mean Square Error (MSE) and regression. The result showed that the average MSE is 0045394Mu and 0.97271 for regression. The implication is that the neural network correctly learns the spacecraft data collected and was able to detect changes in the angular velocity. The step response of the adaptive controller was evaluated with the characterized Proportional Integral Derivative (PID) control system and the result showed that the total time of the attitude determination and control of the spacecraft is 111.24ms as against 465ms with PID which gives 76% reduction in decision time to control error due to dynamics. The comparative analysis with the characterized in the rate of error minimization on the pitch angular velocity showed that the angle was reduced from 13.46mm with the adaptive controller to 9.55mm which gives a percentage improvement of 29%.
    VL  - 8
    IS  - 2
    ER  - 

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Author Information
  • Electrical and Electronics Engineering Department, Enugu State University of Science and Technology (ESUT), Enugu, Nigeria

  • Electrical and Electronics Engineering Department, Enugu State University of Science and Technology (ESUT), Enugu, Nigeria

  • Electrical and Electronics Engineering Department, Enugu State University of Science and Technology (ESUT), Enugu, Nigeria

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