INTECO

 INTECO cung cấp ba chọn lựa phần mềm và phần cứng: MATLAB, LabVIEW, hoặc bất kỳ PLC nào, như SIEMENS chẳng hạn


Có ba nhóm sản phẩm được thiết kế và được chế tạo bởi INTECO

Phần mềm và Thiết bị đào tạo

Chúng tôi, INTECO, mang đến các thiết bị hoàn chỉnh để dạy điều khiển tự động được ứng dụng trong thời gian thực. Các công cụ này cũng có thể được sử dụng để phát triển các giải thuật và các phương pháp điều khiển mới. Mỗi thiết bị thí nghiệm chứa một đơn vị cơ khí, giao tiếp điều khiển và đo lường được trang bị bằng một bo I/O PCI, phần mềm đo lường và điều khiển được thiết kế riêng hoạt động trong môi trường MATLAB/Simulink. Có các sổ tay mô tả làm thế nào để xử lý trong khi thí nghiệm. Các ví dụ hoàn chỉnh được lập trình trước hướng dẫn người dùng thông qua các thí nghiệm thời gian thực.

Các bo I/O và phần mềm được hỗ trợ cho nghiên cứu và đào tạo

Chúng tôi mang đến hai họ bo RT-DAC4/PCI I/O. Một chíp FPGA trên bo có thể cấu hình được và một Logic tiện ích Xilinx khác được mang đến bởi INTECO có thể được lưu trữ. Mỗi lần được lắp đặt trong máy tính bo thích hợp với nhiều ứng dụng đòi hỏi nhiều dạng khác nhau và nhiều kênh I/O. Không cần thiết thay đổi bo cho một ứng dụng mới. Chỉ phần Logic của bo được thay thế.

Đối với người dùng tiên tiến thì Hướng dẫn Lập trình Xilinx có thể được đặt mua. Cho phép tạo ra Logic của riêng mình.

Mỗi bo được trang bị bằng một phần mềm điều khiển ActiveX.

Phần mềm thời gian thực

Hộp công cụ (Toolbox) phát triển chuyên nghiệp RT-CON là một hệ thống điều khiển và thu thập dữ liệu thời gian thực với khả năng truy xuất trực tiếp các kênh I/O và truyền dữ liệu MATLAB. Đây là một công cụ phần mềm thử nghiệm nhanh hướng RTWT để phát sinh tự động các mã bộ điều khiển.
Chúng tôi mang đến gói phần mềm M2ActiveX như là sự giao tiếp giữa MATLAB và các điều khiển ActiveX. 


 Danh sách các Tham khảo (References) đã đăng có sử dụng sản phẩm của INTECO trong nghiên cứu

DC servo motor

Turnau A.: 1998. Prototyping of conventional and intelligent controllers. EAEEIE 98 Lisbon – Enhancement of Education in Electrical and Information Engineering through Industry Co-operation and Research, May 1998, Lisbon, Portugal, pp. 93-98.

Grega W. (1995): A study on the development of integrated environment for small DC servo motor control and simulation, in: Methods and Models in Automatics and Robotics, ed. S.Banka, Wyd. Politechniki Szczeciñskiej, 1995, pp. 371-375.

Hypiusova, M., Osusky, J. and Kajan, S. : Robust Controller Design Using Edge Theorem for Modular Servo System. In: Technical Computing Prague 2007 ,15th Annual Conference Proceedings, Prague, Czech Republic, November 14, ISBN 978-80-7080-658-6.

Ramiro S. Barbosa _, J.A. Tenreiro Machado, Isabel S. Jesus: Effect of fractional orders in the velocity control of a servo system, Computers and Mathematics with Applications 59 (2010) 1679_1686

Dragan Antić, Marko Milojković, Saša Nikolić: Fuzzy sliding mode control with additional fuzzyControl component, Facta Universitatis:Series: Automatic Control and Robotics Vol. 8, No 1, 2009, pp. 25 – 34

Ramiro S. Barbosa, J. A. Tenreiro Machado, Isabel S. Jesus: On the Fractional PID Control of a Laboratory Servo System, Proceedings of the 17th World Congress The International Federation of Automatic Control, Seoul, Korea, July 6-11, 2008

Preitl S.,  Precup R.E., Preitl Z.: Aspects Concerning the Tuning of 2-dof Fuzzy Controllers, Facta Universitatis, Series: Automatic Control and Robotics Vol. 9, No 1, 2010, pp. 1 – 18

Antić D.,  Milojković M., Jovanović Z.,  Nikolić S.: Optimal Design of the Fuzzy Sliding Mode Control for a DC Servo Drive, Strojniški vestnik – Journal of Mechanical Engineering 56(2010)7-8, 455-463 Paper received: 16.01.2009

Horla D., Simulation vs. Experimental Results of Pole-placement Controller with Full Adaptation, Proceedings of the 2013 International Conference on Systems, Control and Informatics, s. 27-33, Venice 2013.

Horla D., Minimum Variance Adaptive Control of A Servo Drive with Unknown Structure and Parameters. Asian Journal of Control, Vol. 15, s. 120.131. doi: 10.1002/asjc.479, 2013.

Horla D., Robust Performance of Sampled-data Adaptive Control of a Servo Drive. From Simulation to Experimental Results, Journal of Automation, Mobile Robotics and Intelligent Systems, Vol. 9(2), 2015, s. 3-8.

Magnetic Levitation

Turnau A., Kolek K.: 1998. Time-optimal and PID variable structure controller. Proceedings of the Mediterranean Conference on Electronics and Automatic Control MCEA’98, Marrakech, 17-19 September, Maroc, pp. 476-479.

A. Rachid,: 1998. A Maglev system for control engineering. Proceedings of the Mediterranean Conference on Electronics and Automatic Control MCEA’98, Marrakech, 17-19 September, Maroc, pp. 488-492.

Piłat A.K.: 2010, Features and Limitations of 2D Active Magnetic Levitation Systems Modeling in COMSOL Multiphysics,  Proceedings of the COMSOL Conference 2010 Paris.

Venayagamoorthy G. K. , Anene E. C.: 2010: PSO Tuned Flatness Based Control of a Magnetic Levitation System. Proceedings of the IEEE Industry Applications Society Annual Meeting, 2010. IAS ’10, Institute of Electrical and Electronics Engineers (IEEE), Oct 2010.
The definitive version is available at http://dx.doi.org/10.1109/IAS.2010.5615717.

Dragos C.A., Preitl S., Precup R.E., Petriu E.M. : 2011, Points of View on Magnetcic Levitation System Laboratory-Based Control Education. In Z.S.Hippe at al.(Eds): Human – Computer Systems Interaction.  AISC 99, Part II, pp. 261-275, Springer Verlag.

Piłat A.K.: 2012: The Programmable Analog Controller. Static and DynamicConfiguration, as exemplified for Active Magnetic Levitation. PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review), ISSN 0033-2097, R. 88 NR 4b/2012

Balko P., Rosinova D.: 2017.  Modeling of magnetic levitation system,  21st International Conference on Process Control (PC), 6-9 June 2017.

Czerwiński K., Ławryńczuk M.: 2017:  Identification of Discrete-Time Model of Active Magnetic Levitation System. In Mitkowski W. at al.(Eds): Trends in Advanced Intelligent Control, Optimisation an Automation. pp. 599 -610, Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 577) , Springer AG 2017.

Tepljakov A.: 2017. Fractional-order Modeling and Control of Dynamic Systems, ISSN 2190-5053 Springer Theses, ISSN 2190-5061 (electronic), pp. 143-153,  Springer International Publishing 2017.

 Bojan-Dragos C.-A.,  Precup R.-E.,  Tomescu M.L., Preitl S.,  Tanasoiu O.-M.,  Hergane S.,: 2017: Proportional-Integral-Derivative Gain-Scheduling Control of a Magnetic Levitation System, INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL ISSN 1841-9836, 12(5), 599-611, October 2017.

Two Rotor Aerodynamical System

Gorczyca P., Hajduk K.: Tracking Control Algorithms for Laboratory Aerodynamical System, International Journal of Applied Mathematics and Computer Science ; ISSN 1641-876X. —2004 vol. 14

Rahideh A., Shaheed M. H.: Mathematical dynamic modeling of a twin-rotor multiple-input multiple-output system. In: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 2007, Vol. 221, February 1, p. 89 – 101.

Madoński R., Herman P.: An Experimental Verification of ADRC Robustness on a Cross-coupled Aerodynamical SystemIndustrial Electronics (ISIE), 2011 IEEE International Symposium on, pp. 859 – 863, 27-30 June 2011, Gdansk

Petko H. Petkov, Nicolai D. Christov,Mihail M. Konstantinov: Robust Real-Time Control of a Two-Rotor Aerodynamic System, Proceedings of the 17th World Congress The International Federation of Automatic Control, Seoul, Korea, July 6-11, 2008

Harlanova E., Yordanova S., Ivanov Z., Dimitrov L.: Multivariable Fuzzy Logic Control of Aerodynamic Plant, Proceedings of the 1st International Conference on Manufacturing Engineering, Quality and Production Systems (Volume II), ISBN: 978-960-474-122-9

Czajkowski A., Patan K.: Designing nonlinear model of the Two Rotor Aero-dynamical System using state space neural networks with delays, Conference: Methods and Models in Automation and Robotics – MMAR 2013 : 18th international conference; ISBN: 978-1-4673-5507-0

Czajkowski A.: Robust Control with Disturbance Estimation Using Echo State Networks for the Twin Rotor Aero-Dynamical System Application. Preprints of the 19th World Congress The International Federation of Automatic Control, Cape Town, South Africa. August 24-29, 2014

Butt S., Aschemann H.: Multivariable Integral Sliding Mode Control of a Two Degrees of Freedom
Helicopter, IFAC-PapersOnLine 48-1 (2015) 802–807.

Pendulum – cart system

Szymkat M., Korytowski A., Turnau A.: Computation of time optimal controls by gradient matchingProc. IEEE Int. Conf. on Control Applications, August 22-27, 1999, Kohala Coast-Island of Hawai’i, USA, TuP1-2, pp. 363-368.

Turnau A.: Fuzzy and rule-based controller for cart-pole system on finite rail. Proc. of the European Conference on Modeling and Simulation, Barcelona , June 1-3, 1994, 460-464.

Turnau A.: From a rule-based to a time-suboptimal controller. Proc. 14th IASTED International Conference: Modelling, Identification and Control, February 20-22, 1995, Igls, Austria, 246-249.

Turnau A., and Korytowski A.: Time optimal control of pendulum-cart system. Sivasundaram S. (edt.) Proc. 1st International Conference on Nonlinear Problems in Aviation & Aerospace, May 9-11 1996, Embry_Riddle Aeronautical University Press, Daytona Beach, Florida, USA, pp. 649-654.

Turnau A., Korytowski A.: Synthesis of time optimal controller for a laboratory pendulum-cart model. Proc. of 16th IASTED International Conference Modeling, Identification and Control, Innsbruck, February 17-19, 1997, 366-371

Turnau A., Korytowski A., Szymkat M.: Time optimal control for the pendulum cart system in real-timeProc. IEEE Int. Conf. on Control Applications, August 22-27, 1999, Kohala Coast-Island of Hawai’i, USA, TuP6-3, pp. 1249-1254.

Grega W., Turnau A.: Time-optimal control of nonlinear systems: new methods and applications. Proc. of Summer School 99, Integrated Control Systems and Intelligent Control, Rzeszów University of Technology, Wetlina, 8-12 June, 1999, pp. 49-75.

Grega W., Turnau A.: 1998. Development of intelligent control algorithms in open architecture environment. Proc. of Summer School ’98 Kraków 7-11 July 1998.

Kempa A., Kolek K., Korytowski A., Tabakowski P, Turnau A.: 1997. Neural time-optimal real-time controller, Proc. 16th IASTED International Conference: Modelling, Identification and Control, February 17-19, Innsbruck, Austria, pp. 214-219.

Turnau A., Korytowski A.: 1996. Time optimal control of pendulum-cart system. Proc. 1st International Conference on Nonlinear Problems in Aviation & Aerospace, May 9-11, Aeronautical University Press, Daytona Beach, Florida 32114, USA, pp. 649-654.

Kolek K., Tabakowski P., Turnau A. 1993. Control of nonlinear system, simulation, real-time control, application of neural networks. Proceedings of the Int. Conference on Modelling Identification and Control. Innsbruck. Austria. pp. 126-127

Mills A., Wills A., Brett N. 2009. Nonlinear Model Predictive Control of an Inverted Pendulum
2009 American Control Conference, Hyatt Regency Riverfront, St. Louis, MO, USA
June 10-12, 2009. 
http://sigpromu.org/mpc/pilot.html

Perev K.: 2011.  Inverted Pendulum Control: an Overview,  Information Technologies and Control ,1.2011, pp.34-41.  http://www.acad.bg/rismim/itc/sub/archiv/Paper5_1_2011.pdf

3DCrane

Weitian Chen, Mehrdad Saif: Output Feedback Controller Design for a Class of MIMO Nonlinear Systems Using High-Order Sliding-Mode Differentiators With Application to a Laboratory 3-D Crane, IEEE Transactions on Industrial Electronics, vol. 55, no. 11, November 2008, 3985

Rigoberto Toxqui, Wen Yu, Xiaoou Li: Anti-swing control for overhead crane with neural compensation, 2006 International Joint Conference on Neural Networks, Vancouver, BC, Canada, July 16-21, 2006

Rigoberto Toxqui , Wen Yu, Xiaoou Li: PD Control of Overhead Crane with Velocity Estimation and Uncertainties Compensation, Proceeding of the 6th World Congress on Control and Automation, June 21 – 23, 2006, Dalian, China

Rigoberto Toxqui Toxqui1, Wen Yu1, and Xiaoou Li: PD Control of Overhead Crane Systems with Neural Compensation, In J. Wang et al. (Eds.): ISNN 2006, LNCS 3972, pp. 1110–1115, Springer-Verlag Berlin Heidelberg 2006

Mariusz Pauluk, Adam Korytowski, Andrzej Turnau, Maciej Szymkat : Time optimal control of 3d crane, MMAR 2001 : Proceedings of the 7th IEEE international conference on Methods and Models in Automation and Robotics : Międzyzdroje 28–31 August 2001. Vol. 2

Masahiro SATO, Shun-ichi AZUMA and Toshiharu SUGIE: Modeling of 3D Crane and Gain Scheduling Control (in Japanese), Proceeding of the 50th Annual Conference of the Institute of Systems, Control and Information Engineers (ISCIE) Kyoto, May 10-12, 2006

Chang-Sei Kim, Keum-Shik Hong: Boundary Control of Container Cranes from the Perspective of Controlling an Axially Moving String System, International Journal of Control, Automation, and Systems (2009) 7(3):437-445, DOI 10.1007/s12555-009-0313-6, http://www.springer.com/12555

Hahn Park, Dongkyoung Chwa, Keum-Shik Hong: A Feedback Linearization Control of Container Cranes: Varying Rope Length, International Journal of Control, Automation, and Systems, vol. 5, no. 4, pp. 379-387, August 2007

Hahn Park, Keum-Shik Hong: Sway Control of Container Cranes as an Axially Moving Nonlinear String,ICCAS2005, June 2-5, KINTEX, Gyeonggi-Do, Korea

Rigoberto Toxqui and Wen Yu,: Systems with velocity estimation and uncertainties compensation, Int. J. Automation and Control, Vol. 1, No. 4, 2007

Floriberto Ortiz Rodriguez, Wen Yu, Marco A. Moreno-Armendariz: Anti-swing control with hierarchical fuzzy CMAC compensation for an overhead crane, 22nd IEEE International Symposium on Intelligent Control Part of IEEE Multi-conference on Systems and Control Singapore, 1-3 October 2007

Zoran Jovanović, Dragan Antić, Zoran Stajić, Miloš Milošević, Saša Nikolić, Staniša Perić: Genetic Algorithms Applied In Parameters Determination Of The 3d Crane Model, Facta Universitatis: Series: Automatic Control and Robotics Vol. 10, No 1, 2011, pp. 19 – 27

Nguyen, Q.T., Veselý, V.: Robust Decentralized PID Controller Design for the 3D Crane Process, Editors: Fikar, M.,Kvasnica, M., In Proceedings of the 18th International Conference on Process Control, Tatranská Lomnica, Slovakia, pp. 485–489, 2011.

Stefan Preitl, Radu-Emil Precup and Zsuzsa Preitl: Case Studies in Teaching Fuzzy and Advanced Control Strategies, Magyar Kutatók 8. Nemzetközi Szimpóziuma 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics 457

Tower Crane

Altaf F.; Modeling and Event-Triggered Control of Multiple 3D Tower Cranes over WSNs, Master’s Degree Project Stockholm,  Sweden October 2010https://pdfs.semanticscholar.org/7afc/b0e72e72d6a01e3c7c2547c7e839100aa41c.pdf

Pauluk M.,  Marchewka D.: 3D Tower Crane as a mechatronic tool for education, 1-st Slovak-Austrian International Conference on Robotics in Education 2011, Bratislava Slovakia, http://ap.urpi.fei.stuba.sk/rie2010/pdf/50.pdf

BREUNING P. : Linear Model Predictive Control of a 3D Tower Crane for Educational Use, Double Master’s Thesis 2015, http://publications.lib.chalmers.se/records/fulltext/219147/219147.pdf

Thein Moe Win, Hesketh T.,  Raymond Eaton R.: Robotic Tower Crane Modeling and Control (RTCMC) with LQR-DRO and LQR-LEIC for Linear and Nonlinear Payload Swing Minimization,  International Review of Automatic Control, Vol 9, No 2 (2016), https://doi.org/10.15866/ireaco.v9i2.8431

ABS system

Dragan Antić, Vlastimir Nikolić, Darko Mitić, Marko Milojković, Staniša Perić: Sliding Mode Control Of Anti-Lock Braking System: An Overview, Facta Universitatis: Series: Automatic Control and Robotics Vol. 9, No 1, 2010, pp. 41 – 58

Oniz Y., Kayacan E., Kaynak O.: A dynamic method to forecast the wheel slip for antilock braking system and its experimental evaluation. IEEE Trans. Syst. Man Cybern. B Cybern. 39(2), 551–560 (2009)

Precup R.E., Spătaru S.V., Rădac M.B., et al.: Model-based fuzzy control solutions for a laboratory antilock braking system. In: Proc. 3rd Int. Conf. On Human System Interaction, Rzeszow, Poland, pp. 133–138 (2010)

Andon V.Topalov, YesimOniz, ErdalKayacan, OkyayKaynak: Neuro-fuzzy control of antilock braking system using sliding mode incremental learning algorithm, Neurocomputing 74 (2011) 1883–1893

Samuel J., Jimoh O.P.: Neural Network-Based Adaptive Feedback Linearization Control of Antilock Braking System, ISSN 0974-0635 International Journal of Artificial Intelligence, Spring (March) 2013, Volume 10, Number S13

MultiTank system

Saša Nikolić, Bratislav Danković, Dragan Antić, Zoran Jovanović: On Identification Of Discrete Systems, FACTA UNIVERSITATIS: Series: Automatic Control and Robotics Vol. 9, No 1, 2010, pp. 59 – 67

Zoran Jovanović, Dragan Antić, Marko Milojković,Saša Nikolić: A New Laboratory Framework for Practical Work in Process Control, Tempus JEP – 41112 – 2006, Workshop I “New Master curricula and EU practice” September 17 – 19, 2008, Niš, Serbia

Mariusz Buciakowski, Marcin Witczak, and Marcel Luzar: Robust Fault-tolerant Control for a Multi-tank System, 11th International Conference on Diagnostics of Processes and Systems , September 2013 , Poland  http://www.researchgate.net/publication/257105901_Robust_Fault-tolerant_Control_for_a_Multi-tank_System

Tepljakov A.: 2017. Fractional-order Modeling and Control of Dynamic Systems, ISSN 2190-5053 Springer Theses, ISSN 2190-5061 (electronic), pp. 131-138,  Springer International Publishing 2017.

Pazera M., Klimkowicz K., Wrzesińska B., Witczak M.: 2017,  A Process Fault-Tolerant Control for Non-linear Dynamic Systems ,  in Advanced Solutions in Diagnostics and Fault Tolerant Control (edited by Kościelny J.M., Syfert M., Sztyber A.:), pp. 34 – 44

Corresponding to RT-CON

GregaW., Kolek K., Turnau A. (1998): „Rapid Prototyping Environment for Real-Time Control Education” Proceedings of the Real-Time Systems Education III, pp. 85-92

Grega W., Kolek K., Turnau A. (1998): „Real-time kernel dedicated to fast mechatronic systems” in: Proceedings of the Mediterranean Conference on Electronics and Automatic Control, pp.480-483


Danh sách các khách hàng trên thế giới sử dụng sản phẩm của INTECO

Aland Islands
  Aland University of Applied Sciences, Mariehamn
Alger
  E.S.L.I SARL, Rouiba
Australia
  University of Melbourne, Victoria; University of New South Wales, Sydney; University of Newcastle, Callaghan; Swinburne University of Technology, Hawthorn
Belgium
  Université Catholique de Louvain
Brasil
  Fundaçao De Desevolvimento Da Pesquisa, Belo Horizonte
Bulgaria
  Fadata Ltd., Sofia; Technical University of Sofia
Canada
  ABB Inc., St-Laurent; Quanser Consulting Inc., Markham; Simon Fraser University, Burnaby; University of Alberta, Edmonton; Université of Sherbrooke, Quebec
China
  Tenfine Limited Company, Beijing; Shanghai Passiontech Information Co.Ltd
Croatia
  University of Zagreb, Zagreb
Czech Republic
  UNIS S. r. o., Brno
Denmark
  Odense Univeristy College; University of Southern Denmark, Sønderborg
Ecuador
  Escuela Politécnica del Ejército, Quito
Egypt
  German University in Cairo – GUC, New Cairo City
Estonia
  Swedish Polytechnic, Vasa; Novia Univerity of Applied Sciences, Vasa
France
  Université de Saint-Jérôme, Marseille; Multitech, Saint Cyr Sur Mer; The Ecole Centrale de Nantes; Université de Picardie Julies Verne, Amiens; Université François-Rabelais Tour; Université Henri Poincare Nancy; Ecole Nationale Supérieure d’Ingénieurs de Limoges; Université de Franche-Comté des Sciences et Techniques, Besancon; Ecole des Mines de Douai
Germany
  Bayerische Julius-Maximilians-Universität Wurzburg; INTEL GMBH, Braunschweig; Technische Universität Illmenau; Technische Universität Kaiserslautern; Universität Rostock; Technische Universität Berlin; Technische Universitat Braunschweig; Ilmenau University of Technology; University of Hannover; Hochschule Offenburg
Greece
  Unique Technology Ltd., Thessaloniki
Holland
  Technische Universiteit Eindhoven
Hungary
  Budapest University of Technology and Economics
India
  Indian Institute of Technology Bombay; University of Mumbai; National Institute of Technology, Tiruchirappalli
Italy
  Italtec S. r. l., Milano; Politecnico Di Bari; Universita’ di Cagliari; Universite degli Studi del Sannio, Benevento; Universita degli Studi di Pavia; Universita degli Studi di Salerno, Fisciano
Iran
  Electronic Afzar Azma Training & Measuring Equipment, Tehran
Japan
  Adtex Co, Ltd, Fujisawa City; Advanced Technology and Systems Co. Ltd., Yokohama; Kyoto University; PID Co. Ltd., Yokohama; Realtec Co., Ltd., Fujisawa City
Korea
  Hanyang University, Seoul; Innotics Inc., South, Kyoung – San City; PNP Tech, Seoul; Pusan National University; Seoul National University; Yeungnam University, Gyeongsan
Kuawait
  Gulf Advanced Trading Company, Safat
Lavita
  University of Latvia, Riga
Malaysia
  Hi-tech Resources, Selangor; Interpac (M) Sdn Bhd, Selangor; Universiti Teknologi Petronas, Tronoh
Mexico
  Centro de Investigación y de Estuidos Avanzados del I.P.N., Mérida, Yucatán; Instituto Tecnológico de Sonora; Universidad Autonoma de San Luis Potosi; Universidad; Autónoma de Nuevo León, San Nicolás de los Garza; Universidad Nacional Autónoma de México; Universidad Regiomontana Mexico, Monterrey; Universidad Autónoma Metropolitana, Mexico City; DSPPROJECTS SA DE CV, Guadalajara; XOCHITL CECILIA ROSAS BARREDA, Puebla
Namibia
  Hüster Machinetool Co. (Pty) Ltd., Windhoek
Netherlands
  Technische Universiteit Eindhove
Oman
  Sultan Qaboos University, Sultanate of Oman
Pakistan
  University of Engineering and Technology, Taxila
Poland
  AB-Micro, Warszawa; AGH University of Science and Technology, Kraków; Agricultural University, Kraków; Białystok Technical University; Cracow University of Technology; Delphi Automotive Systems, Kraków; Eko-Pil, Straszyn; Falmer, Warszawa; Gdańsk University of Technology; INTELWARE, Sandomierz; Koszalin University of Technology; Lublin University of Technology; Maritime University of Gdynia; MERKAR Sp. z o. o., Poznań; Military University of Technology, Warszawa; ONT, Kraków; Opole University of Technology; PWSZ, Tarnów; Poznań University of Technology; Rzeszów University of Technology; Silesian University of Technology, Gliwice; Technical University of Łódź; Valeo, Skawina; Wrocław University of Technology; WSTE, Sucha Beskidzka; Automatyka, Tarnów; University of Zielona Góra; ZSME, Żywiec; MWSZ, Kraków; InFast Sp. z o. o., Rzeszów; Elmark Spółka Jawna Jędrzejewska, Olsztyn; BDI POLAND Sp. z o. o., Straszęcin; Nicolaus Copernicus University, Toruń; Siemens Sp. z o. o. , Warszawa; State Higher School in Przemyśl; University Rzeszów
Portugal
  Institute of Engineering of Porto; Seccao de Sistemas Digitais e Computadores/DEEC, Lisboa
Romania
  ACOR SRL, Timisoara; Politehnica University of Bucharest; Technical University of Cluj – Napoca; Oradea University; Lasting System SRL, Timisoara
Serbia
  Ei ELMIS – Beograd; University of Belgrade
Slovakia
  PPA ENERGO s. r. o., Bratislava
Spain
  Robotnik Automation SLL, Valencia; Universitat Politecnica de Catalunya, Barcelona; Universidad de Murcia; Universidad Del Pais Vasco/Euskal Herriko Unibertsitatea, Bilbao; Universidad Politécnica de Valencia; Universitat de Girona; Universidade de Vigo
Sweden
  Linköping University, Linköping; KTH School of Electrical Engineering, Stockholm
Switzerland
  EPFL, Lausanne; HSR University of Applied Sciences, Rapperswil
Taiwan
  Cho Chieh Tech. Enterprise Ltd., San Chung City
Thailand
  ELWE Co., Ltd., Bangkok
Turkey
  Aselsan Inc.Communications Division, Yenimahalle; FFesto San. ve Tic. A. S., Istanbul; Kagum Teknik Danışmanlık LTD ŞTİ, Istanbul
United Kingdom
  Bytronic International Ltd., Sutton; Feedback Instruments Ltd., Crowborough; University of Reading, Whiteknights
United Arabian Emirates
  American University of Sharjah; Business Communications L.L.C., Dubai; Hatta Trading and Services, Abu Dhabi; Technical Solutions International FZE, Dubai
USA
  Clemson University; Feedback Inc., Hillsborough; Rutgers The State University of New Jersey; University of Utah, Salt Lake City; University of Missouri; Missouri University of Science and Technology, Rolla
   

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