Efficient model of PID controller of unmanned aerial vehicle

Main Article Content

Arsen R. Petrosian
https://orcid.org/0000-0003-0960-8461
Ruslan V. Petrosyan
https://orcid.org/0000-0002-0388-8821
Ihor A. Pilkevych
https://orcid.org/0000-0001-5064-3272
Maryna S. Graf
https://orcid.org/0000-0003-4873-548X

Abstract

The modern stage of science and technology development is distinguished by the widespread use of digital signal processing. The use of digital processing for effective control of aircraft and other technical equipment remains relevant for many industries. The paper considers the problem of building a model of a digital PID-regulator, which can be used in unmanned aerial vehicles. It is proposed to base the regulator on the methods of digital filtering (realisation of the differential component using a digital filter with a finite impulse response). Calculation of digital filter coefficients is performed using genetic algorithm. This approach allows to increase the accuracy of the model, to provide the calculation of PID-regulator coefficients using classical PID-regulator methods. The software on Python programming language realizing the proposed method has been developed. The effectiveness of the developed model is demonstrated in simulation.

Downloads

Download data is not yet available.

Article Details

How to Cite
Petrosian, A.R., Petrosyan, R.V., Pilkevych, I.A. and Graf, M.S., 2023. Efficient model of PID controller of unmanned aerial vehicle. Journal of Edge Computing [Online], 2(2), pp.104–124. Available from: https://doi.org/10.55056/jec.593 [Accessed 24 May 2024].
Section
Articles

How to Cite

Petrosian, A.R., Petrosyan, R.V., Pilkevych, I.A. and Graf, M.S., 2023. Efficient model of PID controller of unmanned aerial vehicle. Journal of Edge Computing [Online], 2(2), pp.104–124. Available from: https://doi.org/10.55056/jec.593 [Accessed 24 May 2024].
Received 2023-07-25
Accepted 2023-10-26
Published 2023-10-30

References

ArduPilot Documentation, 2023. Available from: https://ardupilot.org/ardupilot/.

Atmel, 2016. AVR221: Discrete PID Controller on tinyAVR and megaAVR devices. Available from: http://ww1.microchip.com/downloads/en/AppNotes/Atmel-2558-Discrete-PID-Controller-on-tinyAVR-and-megaAVR_ApplicationNote_AVR221.pdf.

Baikar, P.M., 2014. Design of PID controller based information collecting robot in agricultural field. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(8), pp.11013–11019. Available from: https://doi.org/10.15662/ijareeie.2014.0308012. DOI: https://doi.org/10.15662/ijareeie.2014.0308016

Bhandari, P. and Csurcsia, P.Z., 2022. Digital implementation of the PID controller. Software Impacts, 13, p.100306. Available from: https://doi.org/10.1016/j.simpa.2022.100306. DOI: https://doi.org/10.1016/j.simpa.2022.100306

Borase, R.P., Maghade, D.K., Sondkar, S.Y. and N., P.S., 2021. A review of PID control, tuning methods and applications. International Journal of Dynamics and Control, 9, pp.818–827. Available from: https://doi.org/10.1007/s40435-020-00665-4. DOI: https://doi.org/10.1007/s40435-020-00665-4

Carr, J., 2014. An introduction to genetic algorithms. Available from: https://www.whitman.edu/documents/academics/mathematics/2014/carrjk.pdf.

Graf, M.S., 2020. Unmanned aerial vehicle bypass training system. Technical Engineering, 2(86), pp.81–85. Available from: https://doi.org/10.26642/ten-2020-2(86)-81-85. DOI: https://doi.org/10.26642/ten-2020-2(86)-81-85

Hornsey, S., 2012. A Review of Relay Auto-tuning Methods for the Tuning of PID-type Controllers. Reinvention: an International Journal of Undergraduate Research, 5(2). Available from: http://www.warwick.ac.uk/reinventionjournal/archive/volume5issue2/hornsey.

Hou, D., 2015. PID Control on PIC16F161X by using a PID Peripheral. Available from: http://ww1.microchip.com/downloads/en/AppNotes/90003136A.pdf.

Jayachitra, A. and Vinodha, R., 2014. Genetic Algorithm Based PID Controller Tuning Approach for Continuous Stirred Tank Reactor. Advances in Artificial Intelligence, 2014. Available from: https://doi.org/10.1155/2014/791230. DOI: https://doi.org/10.1155/2014/791230

Kadu, C. and Patil, C., 2016. Design and Implementation of Stable PID Controller for Interacting Level Control System. Procedia Computer Science, 79, pp.737–746. Proceedings of International Conference on Communication, Computing and Virtualization (ICCCV) 2016. Available from: https://doi.org/10.1016/j.procs.2016.03.097. DOI: https://doi.org/10.1016/j.procs.2016.03.097

Maghsadhagh, A., 2016. Implementation of PID controller by microcontroller of PIC (18 Series) and controlling the height of liquid in sources. Advances in Robotics & Automation, 5(3). Available from: https://doi.org/10.4172/2168-9695.1000156. DOI: https://doi.org/10.4172/2168-9695.1000156

Masade, S., Parmar, S. and Bhanushali, A.J., 2016. Speed Control for Brushless DC Motors using PID Algorithm. Available from: https://ru.scribd.com/document/561125158/Speed-Control-for-Brushless-DC-Motor-Using-PID-Algorithm.

Mohamed, N.M., Abdalaziz, A.A., Ahmed, A.A. and Ahmed, A.A., 2017. Implementation of a PID control system on microcontroller (DC motor case study). 2017 international conference on communication, control, computing and electronics engineering (ICCCCEE). IEEE, pp.1–5. Available from: https://doi.org/10.1109/ICCCCEE.2017.7866088. DOI: https://doi.org/10.1109/ICCCCEE.2017.7866088

Mutingi, M. and Mbohwa, C., 2017. Grouping genetic algorithms. Advances and Applications. Springer Cham. Available from: https://doi.org/10.1007/978-3-319-44394-2. DOI: https://doi.org/10.1007/978-3-319-44394-2

Nikitchuk, T.M., Vakaliuk, T.A., Chernysh, O.A., Korenivska, O.L., Martseva, L.A. and Osadchyi, V.V., 2021. Architecture for edge devices for diagnostics of students’ physical condition. In: S.O. Semerikov, ed. Joint Proceedings of the Workshops on Quantum Information Technologies and Edge Computing (QuaInT+doors 2021), Zhytomyr, Ukraine, April 11, 2021. CEUR-WS.org, CEUR Workshop Proceedings, vol. 2850, pp.45–56. Available from: http://ceur-ws.org/Vol-2850/paper3.pdf.

Petrosian, A.R., Petrosian, R.V. and Pidtychenko, O.V., 2021. Optimization of the PID controller model based on a digital filter. Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences, 32(71)(4), pp.129–134. Available from: https://doi.org/10.32838/2663-5941/2021.4/20. DOI: https://doi.org/10.32838/2663-5941/2021.4/20

Petrosian, R., Kuzmenko, O. and Petrosian, A., 2021. Method for calculating the FIR filter based on genetic algorithm. International Scientific Journal “Computer Systems and Information Technologies”, 1, pp.19–24. Available from: https://doi.org/10.31891/CSIT-2021-3-3.

Petrosian, R.V., Pilkevych, I.A. and Petrosian, A.R., 2023. Algorithm for optimizing a PID controller model based on a digital filter using a genetic algorithm. In: T.A. Vakaliuk and S.O. Semerikov, eds. Proceedings of the 3rd Edge Computing Workshop, Zhytomyr, Ukraine, April 7, 2023. CEUR-WS.org, CEUR Workshop Proceedings, vol. 3374, pp.97–111. Available from: https://ceur-ws.org/Vol-3374/paper07.pdf.

Proakis, J.G. and Manolakis, D.K., 2014. Digital Signal Processing. 4th ed. Pearson Education Limited.

PX4 User Guide, 2023. Available from: https://docs.px4.io/main/en/.

Sablina, G.V. and Markova, V.A., 2022. Tuning a PID Controller in a System with a Delayed Second-Order Object. Optoelectronics, Instrumentation and Data Processing, 58, pp.410–417. Available from: https://doi.org/10.3103/S8756699022040112. DOI: https://doi.org/10.3103/S8756699022040112

Samakwong, T. and Assawinchaichote, W., 2016. PID Controller Design for Electrohydraulic Servo Valve System with Genetic Algorithm. Procedia Computer Science, 86, pp.91–94. 2016 International Electrical Engineering Congress, iEECON2016, 2-4 March 2016, Chiang Mai, Thailand. Available from: https://doi.org/10.1016/j.procs.2016.05.023. DOI: https://doi.org/10.1016/j.procs.2016.05.023

Schofield, O.B., Iversen, N. and Ebeid, E., 2022. Autonomous power line detection and tracking system using UAVs. Microprocessors and Microsystems, 94, p.104609. Available from: https://doi.org/10.1016/j.micpro.2022.104609. DOI: https://doi.org/10.1016/j.micpro.2022.104609

Trafczynski, M., Markowski, M., Kisielewski, P., Urbaniec, K. and Wernik, J., 2019. A Modeling Framework to Investigate the Influence of Fouling on the Dynamic Characteristics of PID-Controlled Heat Exchangers and Their Networks. Applied Sciences, 9(5). Available from: https://doi.org/10.3390/app9050824. DOI: https://doi.org/10.3390/app9050824

Yazid, Y., Ez-Zazi, I., Guerrero-González, A., El Oualkadi, A. and Arioua, M., 2021. UAV-Enabled Mobile Edge-Computing for IoT Based on AI: A Comprehensive Review. Drones, 5(4). Available from: https://doi.org/10.3390/drones5040148. DOI: https://doi.org/10.3390/drones5040148

Zhao, J. and Xi, M., 2020. Self-Tuning of PID Parameters Based on Adaptive Genetic Algorithm. IOP Conference Series: Materials Science and Engineering, 782(4), p.042028. Available from: https://doi.org/10.1088/1757-899X/782/4/042028. DOI: https://doi.org/10.1088/1757-899X/782/4/042028

Similar Articles

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)