Rastko Selmic - Concordia University

Research areas: • Consensus and formation control of multi-agent systems • Intelligent control of multi-agent systems • Fault and cyber-attack detection and identification in multi-agent systems • Human-machine interfaces in control

Contact information

Email:

rastko.selmic@concordia.ca

CV:

View Rastko Selmic's CV

Teaching activities

o ENGR 290 – Introductory Engineering Team Design Project

o ELEC 242 – Continuous-Time Signals and Systems

o ELEC 372 – Fundamentals of Control Systems

o ENGR 6121 – Control of Multi-Agent Systems

o ENCS 8011 – Ph.D. Seminar

Publications

Books

R.R. Selmic, V. Phoha, and A. Serwadda, Wireless Sensor Networks: Security, Coverage, and Localization, Springer, 2016

F.L. Lewis, J. Campos, and R. R. Selmic, Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities, SIAM Press, Philadelphia, PA, 2002.

Book Chapters

S. Ramazani, R. R. Selmic, and M. de Queiroz, “Multi-Agent Layered Formation Control Based on Rigid Graph Theory” in Control of Complex Systems:Theory and Applications, K. Vamvoudakis and J. Sarangapani (Eds.), Elsevier2016, pp. 397-419.

D. Jethwa, R. R. Selmic, and F.Figueroa, “Real-time implementation of intelligent actuator control with a transducer health monitoring capability,” in Recent Advances in Control Systems, Robotics, and Automation, S.Pennacchio (Ed.), Third Edition, Internationalsar, Italy, 2009.

R.R. Selmic and F. L. Lewis, “Deadzone compensation in motion control systems using augmented multilayer neural networks,” in Adaptive Control of Systems with Nonsmooth Nonlinearities, G. Tao and F. L. Lewis (Eds.), Springer-Verlag, London, UK, 2001.

R.R. Selmic and F. L. Lewis, “Neural network approximation of piecewise continuous functions: application to friction compensation,” in Soft Computing and Intelligent Systems: Theory and Applications, N. K. Sinha and M. M. Gupta (Eds.), Academic Press, London, UK, 2000.

Journal Papers

R.Babazadeh and R. R. Selmic, “Distributed distance-based formation control in3-D space over directed Laman topologies: Almost global stability,” submitted to the European Journal of Control, July 2026.

N.Elhami Fard, B. Merikhi, R. R. Selmic, and R. McEwen, “Micro multi-agent reinforcement learning systems for tumor therapy: A consensus control approach,” IEEE Access, June 2026. https://doi.org/10.1109/ACCESS.2026.3700084

L.Badran, M. Rahimifard, and R. R. Selmic, “Probabilistic communication for multi-agent consensus: Exact rates and convergence bounds,” IEEE Control Systems Letters (L-CSS), June 2026. https://doi.org/10.1109/LCSYS.2026.3706912

A. M. M. Sizkouhi and R. R. Selmic, “Vision-aligned video diffusion and Doppler-consistent GNSS spoofing: A hybrid covert attack on autonomous vehicles,” submitted to IEEE Transactions on Systems, Man and Cybernetics:Systems, June 2026.

Z.Ebrahimi and R. R. Selmic, “Adaptive gated recurrent unit-based predictive control for directional drilling operations,” submitted to ASME Journal of Dynamic Systems, Measurement and Control, February 2026.

M.Rahimifard and R. R. Selmic, “Zonotope-based leader-following consensus control with cyberattack detection for multiagent systems,” submitted to Automatica, February 2026.

M.Manovic, M. Nikolic, M. Selmic, and R. R. Selmic, “Obstacle-aware energy-efficient routing in wireless sensor networks using an ant colony system,” submitted to the International Journal of Distributed Sensor Networks, Wiley, January 2026.

M. Zareer and R. R. Selmic, “A survey on opinion dynamics in social media networks: Analysis, simulation, and control,” IEEE Transactions on Computational Social Systems, December 2025. https://doi.org/10.1109/TCSS.2025.3622498

A. M. M. Sizkouhi, M. Rahimifard, and R. R. Selmic, “A vision-based covert attack and hybrid adversary detection for autonomous vehicles using generative adversarial network,” IEEE Transactions on Vehicular Technology, October 2025. https://doi.org/10.1109/TVT.2025.3623875

L. Badran, K. Aryankia, and R. R. Selmic,“Multi-agent consensus with non-commensurate time delay: Lambert W function approach,” IEEE Control Systems Letters (L-CSS), vol. 9, pp. 781-786, June 2025. https://doi.org/10.1109/LCSYS.2025.3578272

A. M. M. Sizkouhi and R. R. Selmic, “Diff-VCA: A diffusion-based covert attack on hybrid adversary detection for autonomous vehicles,” submitted to the IEEE Transactions on Intelligent Vehicles, May 2025.

M. Zareer and R. R. Selmic, “Maximizing opinion polarization using double deep Q-learning in social networks,” IEEE Access, vol. 13, January 2025. https://doi.org/10.1109/ACCESS.2025.3537397

R. Babazadeh and R. R. Selmic, “Robust optimal distance-based formation control of uncertain nonlinear agents over directed topologies,” Asian Journal of Control,pp. 1-17, February 2025. https://doi.org/10.1002/asjc.3604

M. Zareer and R. R. Selmic, “Modeling interactions in social media networks using an asynchronous and synchronous opinion dynamics,” Social Network Analysis and Mining, Springer Nature, vol. 14,no. 235, December 2024. https://doi.org/10.1007/s13278-024-01402-x

15. M. Rahimifard, A. M. M. Sizkouhi, and R. R. Selmic,“Cyberattack detection for a class of nonlinear multi-agent systems usingset-membership fuzzy filtering,” IEEE Systems Journal, vol. 18, no. 2, pp.1056-1067, June 2024. https://doi.org/10.1109/JSYST.2024.3359427

K. Aryankia and R. R. Selmic, “Robust adaptive leader-following formation control of nonlinear multi-agents using three-layer neural networks,” IEEE Transactions on Cybernetics, vol. 54, no. 10, pp. 5636-5648, October 2024. https://doi.org/10.1109/TCYB.2024.3356810

17. K. Aryankia and R. R. Selmic, “Neuro-adaptiveformation control of nonlinear multi-agent systems with communication delays,” Journalof Intelligent & Robotic Systems, vol. 109, no. 4, December 2023. https://doi.org/10.1007/s10846-023-02018-7

18. M. Zareer and R. R. Selmic, “Modeling controlagents in social media networks using reinforcement learning,” Special Issueon Innovation in Computing, Engineering Science & Technology in Advances inScience, Technology and Engineering Systems Journal (ASTESJ), vol. 8, no.5, pp. 62-69, November 2023.

19. R. R. Selmic, J. Scoggin, S. Oonk, and F.Maldonado, “Wireless sensor networks fault detection and identification,” InternationalJournal of Robotics and Control Systems, vol. 3, no. 4, pp. 804-823, October2023.

20. N. Elhami Fard, R. R. Selmic, and K. Khorasani, “Areview of techniques and policies on cybersecurity using artificialintelligence and reinforcement learning algorithms,” IEEE Technology andSociety Magazine, vol. 42, no 3, pp. 57-68, September 2023. https://doi.org/10.1109/MTS.2023.3306540

A. Mousavi and R. R. Selmic, “Wearable smart rings for multi-finger gesture recognition using supervised learning,” IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-12, August 2023. https://doi.org/10.1109/TIM.2023.3304703

22. R. Babazadeh and R. R. Selmic, “Directeddistance-based formation control of nonlinear heterogeneous agents in 3-Dspace,” IEEE Transactions on Aerospaceand Electronic Systems, vol. 59, no. 3, pp. 3405-3415, June 2023. https://doi.org/10.1109/TAES.2022.3219039

23. N. Elhami Fard, R. R. Selmic, and K. Khorasani,“Public policy challenges, regulations, oversight, technical, and ethicalconsiderations for autonomous systems: A survey,” IEEE Technology andSociety Magazine, vol. 42, no. 1, pp. 45-53, March 2023. https://doi.org/10.1109/MTS.2023.3241315

N. Elhami Fard and R. R. Selmic, “Adversarial attacks on heterogeneous multi-agent deep reinforcement learning system with time-delayed data transmission,” Journal of Sensor and Actuator Networks, vol. 11, no. 3, September 2022. https://doi.org/10.3390/jsan11030045 (selected as a cover paper)

25. S. A. Mousavi, K. Aryankia, and R. R. Selmic, “Adistributed FDI cyber-attack detection in discrete-time nonlinear multi-agentsystems using neural networks,” European Journal of Control, vol. 66,July 2022. https://doi.org/10.1016/j.ejcon.2022.100646

26. P. Sadhukhan and R. R. Selmic, “Proximal policyoptimization for formation navigation and obstacle avoidance,” InternationalJournal of Intelligent Robotics and Applications, Springer, June 2022. https://doi.org/10.1007/s41315-022-00245-z

27. N. Elhami Fard and R. R. Selmic, “Consensus ofmulti-agent reinforcement learning systems: The effect of immediate rewards,” Journal of Robotics and Control, vol. 3,no. 2, March 2022.

28. E. F. M. Ferreira, J. Viana da Fonseca Neto, and R.R. Selmic, “HDP algorithms for trajectory tracking and formation control of multi-agentsystems,” IEEE Access, March 2022. https://doi.org/10.1109/ACCESS.2022.3156092

29. K. Aryankia and R. R. Selmic, “Neural network-basedformation control with target tracking for second-order nonlinear multi-agentsystems,” IEEE Transactions on Aerospace and Electronic Systems, vol.58, no. 1, pp. 328-341, February 2022.

30. K. Aryankia and R. R. Selmic, “Spectral propertiesof the normalized rigidity matrix for triangular formations,” IEEE ControlSystems Letters (L-CSS), vol. 6, pp. 1154-1159, June 2021. https://doi.org/10.1109/LCSYS.2021.3089136

K. Aryankia and R. R. Selmic, “Neuro-adaptive formation control and target tracking for nonlinear multi-agent systems with time-delay,” IEEE Control Systems Letters (L-CSS), vol. 5, no. 3, pp. 791-796, July 2021.

32. K. Haratiannejadi and R. R. Selmic, “Smart gloveand hand gesture-based control interface for multi-rotor aerial vehicles in a multi-subjectenvironment,” IEEE Access, vol. 8, pp. 227667-227677, December 2020. https://doi.org/10.1109/ACCESS.2020.3045858

R. Babazadeh and R. R. Selmic, “Distance-based multi-agent formation control with energy constraints using SDRE,” IEEE Transactions on Aerospace and Electronic Systems, vol. 56, no. 1, pp. 41-56, February 2020.
A. Gardner, C. Duncan, J. Kanno, and R. Selmic, “On the definiteness of Earth mover’s distance and its relation to set intersection,” IEEE Transactions on Cybernetics, vol. 48, no. 11, pp. 3184-3196, November 2018.
S. Ramazani, R. R. Selmic, and M. S. DeQueiroz, “Rigidity-based multiagent layered formation control,” IEEE Transactions on Cybernetics, vol. 47, no. 8, pp. 1902-1913, August 2017.
S. Ramazani, J. Kanno, R. Selmic, and M. Brust, “Topological and combinatorial coverage hole detection in coordinate-free wireless sensor networks,” International Journal of Sensor Networks, vol. 21, no. 1, pp. 40-52, January 2016.
G. Zhang, C. Duncan, J. Kanno, and R. R. Selmic, “Unmanned ground vehicle navigation in coordinate-free and localization-free wireless sensor and actuator networks,” Journal of Intelligent and Robotic Systems, Springer, vol. 74, no. 3, pp. 869–891, June 2014.
Y. B. Reddy and R. R. Selmic, “A trust-based approach for secure packet transfer in wireless sensor networks,” International Journal on Advances in Security, vol. 4, no. 3-4, December 2011.
O. Kuljaca, J. Gadewadikar, and R. R. Selmic, “Adaptive neural network frequency control for thermopower generators,” International Journal of Robotics and Automation, vol. 26, no. 1, pp. 86-92, February 2011.
R. Selmic, A. Mitra, S. Challa, and N. Simicevic, “Ultra-wideband signal propagation experiments in liquid media,” IEEE Transactions on Instrumentation and Measurement, vol. 59, no. 1, pp. 215-220, January 2010.
D. Jethwa, R. R. Selmic and F. Figueroa, “Real-time implementation of intelligent actuator control with a transducer health monitoring capability,” International Journal of Factory Automation, Robotics, and Soft Computing, no. 1, pp. 5–10, January 2009.

42. A. I. Moustapha and R. R. Selmic, “Wireless sensornetwork modeling using modified recurrent neural networks: application tofailure detection,” IEEE Transactions onInstrumentation and Measurement, vol. 57, no. 5, pp. 981-988, May 2008.

R. Selmic, M. Polycarpou, and T. Parisini, “Actuator fault detection in nonlinear uncertain systems using neural on-line approximation models,” European Journal of Control, vol. 15, no. 1, pp. 29-44, Jan-Feb 2009.
W. Gao and R. R. Selmic, “Neural network control of a class of nonlinear systems with saturation,” IEEE Transactions on Neural Networks, vol. 17, no. 1, pp. 147-156, Jan. 2006.
R. R. Selmic, book review for Automatica, vol. 42, no. 3, March 2006: Adaptive Control Design and Analysis, by Gang Tao, John Wiley & Sons, Inc., Hoboken, New Jersey, 640pp., 2003, ISBN: 0-471-27452-6.
R. R. Selmic, “Discussion on a multi-model approach to failure detection in uncertain sampled-data systems,” European Journal of Control, vol. 11, pp. 266-268, November 2005.
W. Zhou, A. Khaliq, Y. Tang, H.-F. Ji, and R. R. Selmic, “Simulation and design of piezoelectric microcantilever chemical sensors,” Sensors and Actuators A, vol. 125, no. 1, pp. 69-75, October 2005.
R. K. Sunkam, J. S. Hill, R. R. Selmic, and D. T. Haynie, “Solid-state nanopulse generator: application in ultra-wideband bioeffects research,” Review of Scientific Instruments, vol. 76, 054702, May 2005.
Javier Campos, Frank L. Lewis, and Rastko Selmic, “Backlash compensation with filtered prediction in discrete time nonlinear systems by dynamic inversion using neural networks,” Asian Journal of Control, vol. 6, no. 3, pp. 362-375, September 2004.
S. K. Rangarajan, V. V. Phoha, K. Balagani, R. R. Selmic, S. S. Iyengar, “Web user clustering and its application to prefetching using ART neural networks,” IEEE Computer, April 2004.
R. R. Selmic and F. L. Lewis, “Neural network approximation of piecewise continuous functions: application to friction compensation,” IEEE Transactions on Neural Networks, vol. 13, no. 3, pp. 745-751, May 2002.
Rastko R. Selmic and Frank L. Lewis, “Neural net backlash compensation with Hebbian tuning using dynamic inversion,” Automatica, vol. 37, pp. 1269-1277, April 2001.
Rastko R. Selmic and Frank L. Lewis, “Backlash compensation in nonlinear systems using dynamic inversion by neural networks,” Asian Journal of Control, vol. 2., no. 2, pp. 76-87, June 2000.
Javier Campos, Frank L. Lewis, and Rastko Selmic, “Backlash compensation in discrete time nonlinear systems using dynamic inversion by neural networks: a preliminary approach,” Developments in Intelligent Control for Industrial Applications of the Int. Journal of Adaptive Control and Signal Processing, 1999.
Rastko R. Selmic and Frank L. Lewis, “Deadzone compensation in motion control systems using neural networks,” IEEE Trans. Automat. Contr., vol. 45, no. 4, pp. 602-613, April 2000.
F. L. Lewis, K. Liu, R. R. Selmic, and Li-Xin Wang, “Adaptive fuzzy logic compensation of actuator deadzones,” Journal of Robotic Systems, vol. 14, no. 6, pp. 501-511, 1997.

Rastko Selmic, Ph.D.

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