Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 2
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

The paper deals with the problem of position and speed estimation methods in SRM (Switched Reluctance Motor) drive equipped with hysteresis band current controller with MRAS (Model Reference Adaptive System) type observer. An adaptive flux model uses equation set of one-dimensional equations instead of one two-dimensional equation. The reference model is the formal one. Instead of measured current the observer utilizes reference current. Such drive system works well at speed range up to 600 rad/s. The observer's gains must change depend on the speed range. The robustness on motor parameter poor estimation is presented.
Go to article

Authors and Affiliations

Konrad Urbański
Download PDF Download RIS Download Bibtex

Abstract

The paper presents the results of simulations and experiments in the field of control of the low damping and time delay oscillating system. This system includes a quadcopter hovering at a very low altitude, and the altitude is controlled. The time delay is introduced mainly by the remote control device. In order to handle the quadcopter at low altitudes, a proportional-integral controller with a negative proportional coefficient is used. Such an approach can provide good results in the case of an oscillating, low damped system. This method of steering, which uses a typical radio control transmitter, can be used on any commercially available leisure drone. Feedback is provided by a camera and algorithms of computer vision. The presented results were obtained experimentally using free flight – without a harness. Different types of controllers are used to control horizontal shift and altitude.
Go to article

Bibliography

[1] Hu Y., Wu B., Vaughan J., Singhose W., Oscillation suppressing for an energy efficient bridge crane using input shaping, 9th Asian Control Conference (ASCC), IEEE, pp. 1–5 (2013), DOI: 10.1109/ASCC.2013.6606196.
[2] Watanabe K., Yoshikawa M., Ishikawa J., Damping control of suspended load for truck cranes in consideration of second bending mode oscillation, in IECON 2018 – 44th Annual Conference of the IEEE Industrial Electronics Society, IEEE, pp. 4561–4568 (2018), DOI: 10.1109/IECON.2018.8591232.
[3] Nowicki M., Respondek W., Piasek J., Kozłowski K., Geometry and flatness of m-crane systems, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 67, no. 5, pp. 893–903 (2019), DOI: 10.24425/BPASTS.2019.130872.
[4] Cheeseman I., BennettW., The Effect of the Ground on a Helicopter Rotor in Forward Flight, Ministry of Supply, Aeronautical Research Council, Reports and Memoranda, A.R.C. Technical Report R.&M., no. 3021 (1957).
[5] Sharf I., Nahon M., Harmat A., Khan W., Michini M., Speal N., Trentini M., Tsadok T., Wang T., Ground effect experiments and model validation with Draganflyer x8 rotorcraft, in 2014 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1158–1166 (2014), DOI: 10.1109/ICUAS.2014.6842370.
[6] Kan X., Thomas J., Teng H., Tanner H.G., Kumar V., Karydis K., Analysis of Ground Effect for Small- Scale UAVs in Forward Flight, IEEE Robotics and Automation Letters, vol. 4, no. 4, pp. 3860–3867 (2019), DOI: 10.1109/LRA.2019.2929993.
[7] Xuan-Mung N., Hong S.-K., Barometric Altitude Measurement Fault Diagnosis for the Improvement of Quadcopter Altitude Control, 19th International Conference on Control, Automation and Systems (ICCAS), Jeju, Korea (South), pp. 1359–1364 (2019), DOI: 10.23919/ICCAS47443.2019.8971729.
[8] Xuan-Mung N., Hong S.-K., Nguyen N.P., Le Nhu Ngu Thanh Ha, Le T.L., Autonomous Quadcopter Precision Landing Onto a Heaving Platform: New Method and Experiment, IEEE Access, vol. 8, pp. 167192–167202 (2020), DOI: 10.1109/ACCESS.2020.3022881.
[9] Xian B., Liu Y., Zhang X., Cao M., Wang F., Hovering control of a nano quadrotor unmanned aerial vehicle using optical flow, in Proceedings of the 33rd Chinese Control Conference 2014, pp. 8259–8264 (2014), DOI: 10.1109/ChiCC.2014.6896384.
[10] Scerri J., Djordjevic G.S., Todorovic D., Modeling and control of a reaction wheel pendulum with visual feedback, in 2017 International Conference on Control, Automation and Diagnosis (ICCAD), pp. 024–029 (2017), DOI: 10.1109/CADIAG.2017.8075625.
[11] Ito K., Yamakawa Y., Ishikawa M.,Winding manipulator based on high-speed visual feedback control, in 2017 IEEE Conference on Control Technology and Applications (CCTA), pp. 474–480 (2017), DOI: 10.1109/CCTA.2017.8062507.
[12] Cheng H., Lin L., Zheng Z., Guan Y., Liu Z., An autonomous vision-based target tracking system for rotorcraft unmanned aerial vehicles, in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1732–1738 (2017), DOI: 10.1109/IROS.2017.8205986.
[13] Dong Q., Zou Q., Visual UAV detection method with online feature classification, in 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), pp. 429–432 (2017), DOI: 10.1109/ITNEC.2017.8284767.
[14] Viola P., Jones M., Rapid object detection using a boosted cascade of simple features, in Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. I.511–I.518 (2001), DOI: 10.1109/CVPR.2001.990517.
[15] Urbanski K., Visual Feedback for Control using Haar-Like Classifier to Identify the Quadcopter Position, in International Conference on Methods and Models in Automation and Robotics MMAR (2018), DOI: 10.1109/MMAR.2018.8485886.
[16] Bouabdallah S., Siegwart R., Backstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor, in Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, pp. 2247–2252 (2005), DOI: 10.1109/ROBOT.2005.1570447.
[17] Dikmen I.C., Arisoy A., Temeltas H., Attitude control of a quadrotor, in 2009 4th International Conference on Recent Advances in Space Technologies, pp. 722–727 (2009), DOI: 10.1109/RAST.2009.5158286.
[18] Astudillo A., Muñoz P., Álvarez F., Rosero E., Altitude and attitude cascade controller for a smartphone-based quadcopter, in 2017 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1447–1454 (2017), DOI: 10.1109/ICUAS.2017.7991400.
[19] GiernackiW., Iterative Learning Method for In-Flight Auto-Tuning of UAV Controllers Based on Basic Sensory Information, Applied Sciences, vol. 9, no. 4, p. 648 (2019), DOI: 10.3390/app9040648.
[20] Shang B., Liu J., Zhang Y., Wu C., Chen Y., Fractional-order flight control of quadrotor UAS on vision-based precision hovering with larger sampling period, Nonlinear Dynamics, vol. 97, no. 2, pp. 1735–1746 (2019), DOI: 10.1007/s11071-019-05103-5.
[21] Sadalla T., Horla D., Giernacki W., Kozierski P., Influence of time delay on fractional-order PIcontrolled system for a second-order oscillatory plant model with time delay, Archives of Electrical Engineering, vol. 66, no. 4, pp. 693–704 (2017), DOI: 10.1515/aee-2017-0052.
[22] Gonzalez-Hernandez I., Salazar S., Lopez R., Lozano R., Altitude control improvement for a Quadrotor UAV using integral action in a sliding-mode controller, in 2016 International Conference onUnmanned Aircraft Systems (ICUAS), pp. 711–716 (2016), DOI: 10.1109/ICUAS.2016.7502674.
[23] Wei P., Chan S.N., Lee S., Kong Z., Mitigating ground effect on mini quadcopters with model reference adaptive control, International Journal of Intelligent Robotics and Applications, vol. 3, no. 3, pp. 283–297 (2019), DOI: 10.1007/s41315-019-00098-z.
[24] Lopez-Franco C., Gomez-Avila J., Alanis A.Y., Arana-Daniel N., Villaseñor C., Visual Servoing for an Autonomous Hexarotor Using a Neural Network Based PID Controller, Sensors, vol. 17, no. 8, p. 1865 (2017), DOI: 10.3390/s17081865.
[25] Almeshal A.M., Alenezi M.R., A Vision-Based Neural Network Controller for the Autonomous Landing of a Quadrotor on Moving Targets, Robotics, vol. 7, no. 4, p. 71 (2018), DOI: 10.3390/robotics7040071.
[26] Levine W.S., Ed., The Control Handbook, CRC Press, Inc., Ashwin J. Shah, Jaico Publishing House, 121, M.G. Road, Mumbai – 400 023 (1999).
[27] Urbanski K., Zawirski K., Improved Method for Position Estimation Using a Two-Dimensional Scheduling Array, Automatika – Journal for Control, Measurement, Electronics, Computing and Communications, vol. 56, no. 3, pp. 331–340 (2015), DOI: 10.7305/automatika.2015.12.732.
[28] PL-Grid Infrastructure – Welcome – Infrastruktura PL-Grid: www.plgrid.pl/en.

Go to article

Authors and Affiliations

Konrad Urbański
1
ORCID: ORCID

  1. Institute of Robotics and Machine Intelligence, Poznan University of Technology, Piotrowo 3A str., 60-965 Poznan, Poland

This page uses 'cookies'. Learn more