Dr. Constantin Volosencu

Professor
Department of Automation and Applied Informatics, Politehnica University of Timisoara, Romania


Highest Degree
Doctorat in Control Systems from University of Timisoara, Romania

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Biography

Dr. Constantin Volosencu holds a position of Professor at Politehnica University of Timisoara, Romania. He has completed his Ph.D. in Control System from University of Timisoara, Romania. He is also serving as member of editorial board in number of journals and member of several conference committees. His research interest is in Linear Control Systems, Fuzzy Control, Neural Networks, and control of Electrical Drives, Modeling, Simulation, Identification and Sensor Networks. He is author of 10 book, editor of 7 books and more than 150 scientific papers published at international conferences and journals. He participated in 52 research projects and manager of over 45 national and international research projects. Dr. Constantin worked from 1981 to 1990 at Electrotimis Enterprise Timisoara, in the field of the control systems for industrial machines, where he developed control equipments for a large scale of machineries, which are the objects of 27 patents.

Area of Interest:

Physical Science Engineering
Control System
Sensors
Fuzzy Logic
Neural Network

Selected Publications

  1. Volosencu, C., 2022. Study of the angular positioning of a rotating object based on some computational intelligence methods. Mathematics 10.3390/math10071157.
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  2. VoloÅŸencu, C., 2021. Stability Analysis of Systems with Fuzzy PI Controllers Applied to Electric Drives. Mathematics, Vol. 9. 10.3390/math9111246.
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  3. VoloÅŸencu, C., 2021. A comparative analysis of some methods for wind turbine maximum power point tracking. Mathematics, Vol. 9. 10.3390/math9192399.
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  4. Volosencu, C., 2021. Reducing energy consumption and increasing the performances of AC motor drives using fuzzy PI speed controllers. Energies, 10.3390/en14082083.
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  5. Curiac, D.I. and C. Volosencu, 2019. A generic method to construct new customized-shaped haotic systems using the relative motion concept. Nonlinear Anal. Modell. Control, 21: 413-423.
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  6. Curiac, D.I., O. Banias, C. Volosencu and C.D. Curiac, 2018. Novel bioinspired approach based on chaotic dynamics for robot patrolling missions with adversaries. Entropy, 10.3390/e20050378.
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  7. Curiac, D.I. and C. Volosencu, 2015. Path planning algorithm based on arnold cat map for surveillance UAVs. Defence Sci. J., 65: 483-488.
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  8. Curiac, D.I. and C. Volosencu, 2015. Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries. Bioinspiration biomimetics, 10: 056017-56017.
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  9. Curiac, D.I. and C. Volosencu, 2015. Imparting protean behavior to mobile robots accomplishing patrolling tasks in the presence of adversaries. Bioinspir. Biomim., 10.1088/1748-3190/10/5/056017.
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  10. Curiac, D.I. and C. Volosencu, 2014. A 2D chaotic path planning for mobile robots accomplishing boundary surveillance missions in adversarial conditions. Commun. Nonlinear Sci. Numer. Simul., 19: 3617-3627.
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  11. Volosencu, C. and D.I. Curiac, 2013. Efficiency improvement in multi-sensor wireless network based estimation algorithms for distributed parameter systems with application at the heat transfer. EURASIP J. Adv. Signal Proces., Vol. 4. 10.1186/1687-6180-2013-4.
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  12. Volosencu, C., 2012. Tuning Fuzzy PID Controllers. In: Theory, Tuning and Application to Frontier Areas, Panda, R.C. (Ed.). InTech, Croatia.

  13. Volosencu, C., 2012. New Technologies: Trends, Innovations and Research. Intech, Rijeka, Croatia.

  14. Volosencu, C., 2012. Cutting Edge Research in New Technologies. Intech, Rijeka, Croatia.

  15. Volosencu, C., 2012. Applying the Technology of Wireless Sensor Network in Environment Monitoring. In: Cutting Edge Research in New Technologies, Volosencu, C. (Ed.). Intech, Croatia, pp: 97-116.

  16. Curiac, D.I. and C. Volosencu, 2012. Ensemble based sensing anomaly detection in wireless sensor networks. Exp. Syst. Applic., 39: 9087-9096.
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  17. Curiac, D.I. and C. Volosencu, 2012. Chaotic trajectory design for monitoring an arbitrary number of specified locations using points of interest. Mathemat. Problems Eng., Vol. 2012. .
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  18. Volosencu, C., 2010. Identification of Distributed Parameter Systems, Based on Sensor Networks. In: Introduction to PID Controllers, Theory, Tuning and Application to Frontier Areas, Panda, R.C. (Ed.). Intech, Rijeka, Croatia, pp: 369-394.

  19. Volosencu, C., 2010. Algorithms for estimation in distributed parameter systems based on sensor networks and ANFIS. WSEAS Trans. Syst., 9: 283-294.
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  20. Curiac, D.L., O. Banias and C. Volosencu, 2010. Implementing time series identification methodology using wireless sensor networks. WSEAS Trans. Comput., 9: 309-318.
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  21. Volosencu, C., 2009. Pseudo-equivalence of fuzzy PID controllers. WSEAS Trans. Syst. Control, 4: 163-176.
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  22. Volosencu, C., 2009. Properties of fuzzy systems. WSEAS Trans. Syst., 8: 210-228.
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  23. Volosencu, C., 2009. Methods for Parameter Estimation and Frequency Control of Piezoelectric Transducers. In: Automation and Control: Theory and Practice, Rodic, A.D. (Ed.). In-Tech, Vienna, Rijeka, pp: 115-136.

  24. Plastoi, M., C. Volosencu, O. Banias, R. Tudoroiu, D.I. Curiac and A. Doboli, 2009. Integrated system for malicious node discovery and self-destruction in wireless sensor networks. Int. J. Adv. Networks Serv., 2: 241-250.
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  25. Curiac, D.I., C. Volosencu, D. Pescaru, L. Jurca and A. Doboli, 2009. Redundancy and its applications in wireless sensor networks: A survey. WSEAS Trans. Comput., 8: 705-714.

  26. Volosencu, C., 2008. Stabilization of fuzzy control: Systems. WSEAS Trans. Syst. Control, 3: 879-896.
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  27. Volosencu, C., 2008. Identification of distributed parameter systems, based on sensor networks and artificial intelligence. WSEAS Trans. Syst., 7: 785-801.
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  28. Volosencu, C., 2008. Control of electrical drives based on fuzzy logic. WSEAS Trans. Syst. Control, 3: 809-822.
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  29. Fuiorea, D., V. Gui, D. Pescaru, P. Paraschiv, I. Codruta, D. Curiac and C. Volosencu, 2008. Video-based wireless sensor networks localization technique based on image registration and sift algorithm. WSEAS Trans. Comput., 7: 990-999.

  30. Curiac, D.I., C. Volosencu, A. Doboli, O. Dranga and T. Bednarz, 2007. Discovery of malicious nodes in wireless sensor networks using neural predictors. WSEAS Trans. Comput. Res., 2: 38-43.
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