Brain-computer interface for control of electro-hydraulic servo drive

• Autorzy: Wos P. , Dindorf R.

Identyfikatory

DOI

10.5604/01.3001.0012.7635

• Języki publikacji: EN

Abstrakty

EN

The aim of the study was to perform bioelectric signal analysis focusing on its applicability to control of the electro-hydraulic servo drive. The natural bioelectric signals generated by brain, facial muscles and eye muscles read by the NIA (Neural Impulse Actuator) are translated into control commands in the controller of electro-hydraulic servo drive. Bioelectric signals detected by means of special forehead band with three sensors are sent to the actuator box, where they are interpreted as control signals. The test stand was constructed to control of the electro-hydraulic servo drive by means of bioelectric signals generated by the operator. The control signals from the actuator box are transmitted via a wireless network to the controller of electro-hydraulic positioning drive.

Słowa kluczowe

EN

electro-hydraulic positioning system; biosignal processing; parallel manipulator

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2018
• Tom: Vol. 18, No. 4
• Strony: 86--95
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Wos P.

• Faculty of Mechatronics and Machine Design, Kielce University of Technology, Kielce, Poland

autor

Dindorf R.

• Faculty of Mechatronics and Machine Design, Kielce University of Technology, Kielce, Poland

Bibliografia

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• [2] GNANAYUTHAM P., GEORGE J., 2007, Inclusive design for Brain Body Interfaces, D.D. Schmorrow, L.M. Reeves (Eds.), Foundations of Augmented Cognition, Springer Verlag, 103-112.
• [3] AHMADNEZHAD M., SOLTANPOUR M., 2015, Tracking performance evaluation of robust back-stepping control design for a nonlinear electrohydraulic servo system, World Academy of Science, Engineering and Technology International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 9/7, 1341-1347.
• [4] KHEOWREE T., KUNTANAPREEDA S., 2015, Adaptive dynamic surface control of an electrohydraulic actuator with friction compensation, Asian Journal of Control, 17, 855-867, DOI: 10.1002/asjc.935.
• [5] Catalogue allison hydraulics, 2014, http://www.allisonhydraulics.com/x/img/products/ah_catalogue.pdf
• [6] LIU Z., DONG X., XUE J., ZHANG L., 2015, Adaptive tracking control for nonlinear systems with a class of input nonlinearities, Asian Journal of Control, DOI: 10.1002/asjc.1085.
• [7] MERCORELLI P., 2015, Robust adaptive soft landing control of an electromagnetic valve actuator for camless engines, Asian Journal of Control, doi: 10.1002/asjc.1250.
• [8] TAKOSOGLU J., ŁASKI P., BŁASIAK S., 2012, A fuzzy logic controller for the positioning control of an electro-pneumatic servo-drive, Proceedings of the Institution of Mechanical Engineers, Part I-Journal of Systems and Control Engineering, 226/I10, 1335-1343.
• [9] TAKOSOGLU J.E., LASKI P.A., BLASIAK S., 2014, Innovative modular pneumatic valve terminal with self-diagnosis, control and network communications, Edited by FUIS V., Proceedings of 20th International Conference on Engineering Mechanics 2014, Brno University of Technology, 644-647.
• [10] HAGEDOORN H., OCZ NIA Review – Neural impulse actuator, http://www.guru3d.com/articles-pages/ocz-nia-review-neural-impulse-actuator,1.html.
• [11] REYNOLDS B., WAECHTER A., 2009, Brain computer interfacing using the Neural Impulse Actuator, A usability and statistical evaluation, California Polytechnic State University.
• [12] DINDORF R., WOŚ P., 2015, Brain computer interface for wireless remote control, MCSB’2015 – International Conference Cybernetic Modelling of Biological Systems, Krakow, DOI: 10.1515/bams-2015-0011, 15-16.

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).