COMPUTER-INTEGRATED SYSTEM FOR IMITATING THE AVIONICS CARRIER MOTIONS IN LABORATORY CONDITIONS

Authors

DOI:

https://doi.org/10.32782/mathematical-modelling/2024-7-2-12

Keywords:

computer-integrated system, simulation, synthesis, filter, Stewart platform, software, servomotors, interface, Matlab, Simulink

Abstract

The article is devoted to developing the methodology for creating the avionics carrier motions computer-integrated reproducing system in laboratory conditions using the Stewart platform with a help of the Simulink tools from the Matlab environment. The development and implementation of this methodology will allow to overcome the contradiction between the conditions of certification of avionics and the conditions of their operation at a real facility. In turn, overcoming this contradiction will significantly increase the accuracy of measuring flight parameters. The studying object is a Stewart platform prototype. The subject of the study is to determine the software and hardware means of simulating the spatial motion of an autonomous underwater unmanned mobile object as an avionics carrier. This article uses the optimal multidimensional filters for stochastic processes formation synthesis methods, visual object-oriented programming and analytical mechanics of parallel kinematics devices. Based on the analysis literary sources, the platformless inertial navigation system error characteristics dependence on the its carrier motions nature is shown. The technique is substantiated and its application is presented for creating a motion simulator of such a carrier based on the Stewart platform mock-up. This technique consists of six elements: interface controller choice for the Matlab software environment communication with the Stuart platform servomotors; installation and configuration of the selected controller for the Simulink tool software support package; structure and parameters synthesis of the Simulink model for the Stewart platform control signal generation subsystem; Simulink model for the solving the inverse kinematics problem subsystem development; subsystem for determining the drive motors rotation angles Simulink model development; platform motion control subsystem Simulink model development. The developed methodology allows designing and creating simulators of navigation information measuring device carrier in space stochastic movements based on the Stewart platform. This makes it possible to perform measuring devices dynamic characteristics certification in conditions close to real ones. The only limitation of the new methodology application is the requirement of matching the platform drives bandwidth and the practical width of the program signal spectrum.

References

Блохін Л. М., Осадчий С. І., Дідик О. К. та ін. Технології конструювання сучасних конкурентоспроможних комплексів керування стохастичним рухом об’єктів : монографія. Кропивницький : Видавець Лисенко. 2023.

Зозуля В. А., Осадчий С. І., Мельніченко М. М. Аналіз характеристики точності відтворення еталонної траєкторії платформою Гауфа-Стюарта з системою управління для різних видів завдань. Центральноукраїнський науковий вісник. Технічні науки, 2019, вип. 1(32). С. 211–219.

Review and selection of commercially available IMU for a short time inertial navigation. Borodacz, Krystian & Szczepanski, Cezary & Popowski, Stanisław. URL: https://www.researchgate.net/publication/353464312_Review_and_selection_of_commercially_available_IMU_for_a_short_time_inertial_navigation. (дата звернення 04.12.2024).

Осадчий С. І., Дяченко М. М. Збір та первинна обробка даних з системи ARDUPILOT для ідентифікації моделі динаміки квадрокоптеру. Науковий журнал «Прикладні питання математичного моделювання». 2020. Т. 3. № 2.1. С. 197–205.

Ahmed Radi, Sameh Nassar, and Naser El-Sheimy Stochastic Error Modeling of Smartphone Inertial Sensorsfor Navigation in Varying Dynamic Conditions. Gyroscopy and Navigation. 2018. Vol. 9. No. 1. P. 76–95.

Aliev F.A., Bordyug V.A., Larin V.B.: Factorisation of polynomial matrices with respect to imaginary axis and unit circle. Avtomatika. 1989. No. 4. P. 51–58.

Arduino Mega 2560. WEB-сайт. URL: https://doc.arduino.ua/ru/hardware/Mega2560 (дата звернення 7.11.2024).

Bellman, R. Introduction to Matrix Analysis. 2nd edn. SIAM, Philadelphia (1997). 412 p.

El-Sheimy N., Hou H., Niu X. Analysis and modeling of inertial sensors using Allan variance. IEEE Transactions on Instrumentation and Measurement. 2008. vol. 57. no. 1. P. 140–149.

Evans J.R. et al., Method for calculating self-noise spectra and operating ranges for seismographic inertial sensors and recorders. Seismological Research Letters. 2010. vol. 81. no. 4. P. 640–646.

Guerrier S., Skaloud J., Stebler Y., Victoria-Feser M.-P. Wavelet-variance-based estimation for composite stochastic processes. Journal of the American Statistical Associa-tion. 2013. vol. 108. no. 503. P. 1021–1030.

Inverse Kinematics of a Stewart Platform. URL: https://raw.org/research/inverse-kinematics-ofa-stewart-platform (дата звернення 07.11.2024).

Installing Hardware support packages : Step-by-step procedure to get started. URL: https://ieee-tems-blogs.medium.com/hardware-support-packages-using-simulink-to-create-arduinoprojects-5759be619d9c (дата звернення 07.11.2024).

Li Y., Georgy J., Niu X., Li Q., El-Sheimy. Autonomous calibration of MEMS gyros in consumer portable devices. IEEE Sensors Journal. 2015. vol. 15. no. 7. P. 4062–4072.

Moir I., Seabridge A., Jukes M. Civil avionic systems: 2nd edition. West Sussex: John Wiley & Sons, Ltd., 2013. 551 p.

Mosterman, Pieter Prabhu, Sameer Dowd, Andrew Glass, John Erkkinen, Tom Kluza, John Shenoy, Rohit. Embedded real-time control via MATLAB, Simulink, and xPC Target. 2005. DOI 10.1007/0-8176-4404-0_18.

Osadchy S., Prokophyeva I.: Multidimensional autonomous object structural identification on the base of it’s disturbed motion. Gyrotechnology, Navigation, Movement Control and Aerospace Technic Engineering: materials of the VI International Conference. Reports Part II. Kyiv, Ukraine. 2007. p. 17–24.

Osadchy S.I., Zozulya V.A., Rudiuk G. I. The Dynamics of 3-dimentional micro-mechanic sensor of angle motions of a robot-hexapod. International Conference on. Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2015) : Proceedings of the 8th IEEE. Vol. 2. Warsaw, Poland 2015. pp. 908–912.

Rizvi I.H., Udayraj. A modified Kalman filter-based model for core temperature estimation during exercise and recovery with/without personal cooling interventions. J Therm Biol. 2022. 109. 103307. doi:10.1016/j.jtherbio.2022.103307

Sabatini R. The Future of Avionics Systems. R. Sabatini, 2021 IEEE Aerospace & ELECTRONICS SYSTEMS SOCIETY, Virtual Distinguished Lecture Webinar Series. P. 1–63. URL: https://ieeeaess.org/tech-ops/avionics-systems-panel-asp (Дата звернення 11.01.2024).

State Space. URL: https://ch.mathworks.com/help/control/ref/ss.html (дата звернення 1.11.2024).

Stewart D. A Platform with Six Degrees of Freedom. Proc. Instn. Mech. Engrs. 1965–66, Vol. 180, Pr. 1. No 15. Pp. 371–386.

TowerPro SG90 – Micro Servo. URL: https://datasheetspdf.com/pdf-file/791970/TowerPro/SG90/1 (last accessed 2024/01/11).

Transfer Functions TF. URL: https://ch.mathworks.com/help/control/ug/transfer-functions.html (last accessed 2024/01/11)

Using Matlab-Simulink RTW to Build Real Time Control Applications in User Space with RTAILXRT. URL: https://www.rtai.org/userfiles/documentation/documents/ quaranta_mantegazza.pdf ( last accessed 2024/01/11).

Using Stewart Platform as a tool to understand key robotic concepts. URL: https://github.com/Yeok-c/Stewart_Py/blob/main/01_Stewart_Py_Inverse_ Kinema-tics.ipynb (last accessed 2024/11/03).

Zero-pole-gain model ZPK. URL: https://www.mathworks.com/help/control/ref/zpk.html. (last accessed 2024/01/11).

Published

2024-12-30