Skip to main content

Hamid Taghavifar

Assistant Professor, Mechanical, Industrial and Aerospace Engineering


Hamid Taghavifar
Office: S-EV 004.207  
Engineering, Computer Science and Visual Arts Integrated Complex,
1515 St. Catherine W.
Phone: (514) 848-2424 ext. 4261
Email: hamid.taghavifar@concordia.ca

Teaching activities

MECH411: Instrumentation and Measurements

MIAE 215: Programming for Mechanical and Industrial Engineers


Publications

Selected Peer-Reviewed Publications

1. Shojaei, K., & Taghavifar, H. (2022). Input-output feedback linearization control of a tractor with n-trailers mechanism considering the path curvature. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 236(17), 9700-9715.2
2. Taghavifar, H., Rakheja, S., & Reina, G. (2021). A novel optimal path-planning and following algorithm for wheeled robots on deformable terrains. Journal of Terramechanics, 96, 147-157.
3. Taghavifar, H., Qin, Y., & Hu, C. (2021). Adaptive immersion and invariance induced optimal robust control of unmanned surface vessels with structured/unstructured uncertainties. Ocean Engineering, 239, 109792.
4. Shirzadeh, M., Amirkhani, A., Tork, N., & Taghavifar, H. (2021). Trajectory tracking of a quadrotor using a robust adaptive type-2 fuzzy neural controller optimized by cuckoo algorithm. ISA transactions, 114, 171-190.
5. Zhao, Z., Taghavifar, H., Du, H., Qin, Y., Dong, M., & Gu, L. (2021). In-wheel motor vibration control for distributed-driven electric vehicles: A review. IEEE Transactions on Transportation Electrification, 7(4), 2864-2880.
6. Taghavifar, H., & Taghavifar, H. (2021). Adaptive robust control-based energy management of hybrid PV-Battery systems with improved transient performance. International Journal of Hydrogen Energy, 46(10), 7442-7453.
7. Taghavifar, H. (2021). EKF estimation based PID Type-2 fuzzy control of electric cars. Measurement, 173, 108557.
8. Taghavifar, H. (2021). A novel energy harvesting approach for hybrid electromagnetic-based suspension system of off-road vehicles considering terrain deformability. Mechanical Systems and Signal Processing, 146, 106988.
9. Taghavifar, H., Hu, C., Qin, Y., & Wei, C. (2020). EKF-neural network observer based type-2 fuzzy control of autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems, 22(8), 4788-4800.
10. Mohammadzadeh, A., & Taghavifar, H. (2020). A novel adaptive control approach for path tracking control of autonomous vehicles subject to uncertain dynamics. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 234(8), 2115-2126.
11. Taghavifar, H., Xu, B., Hu, C., Qin, Y., & Wei, C. (2020). Commercial vehicle-based robust control of seated whole-body vibration using adaptive indirect type-2 fuzzy neural network. IEEE Access, 8, 124949-124960.
12. Taghavifar, H., Hu, C., Taghavifar, L., Qin, Y., Na, J., & Wei, C. (2020). Optimal robust control of vehicle lateral stability using damped least-square backpropagation training of neural networks. Neurocomputing, 384, 256-267.
13. Mohammadzadeh, A., & Taghavifar, H. (2020). A robust fuzzy control approach for path-following control of autonomous vehicles. Soft Computing, 24(5), 3223-3235.
14. Taghavifar, H., & Rakheja, S. (2020). A methodology to analyze the vehicle vibration response to deformable terrain stiffness and damping properties. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 234(4), 1123-1136.
15. Taghavifar, H. (2020). Reduced vibration of off-road vehicle nonlinear suspension system using an adaptive integral sliding mode-neural network controller. International Journal of Dynamics and Control, 8(1), 291-301.
16. Taghavifar, H. (2019). Neural network autoregressive with exogenous input assisted multi-constraint nonlinear predictive control of autonomous vehicles. IEEE Transactions on Vehicular Technology, 68(7), 6293-6304.
17. Taghavifar, H., & Rakheja, S. (2019). A novel terramechanics-based path-tracking control of terrain-based wheeled robot vehicle with matched-mismatched uncertainties. IEEE Transactions on Vehicular Technology, 69(1), 67-77.
18. Hu, C., Wang, Z., Taghavifar, H., Na, J., Qin, Y., Guo, J., & Wei, C. (2019). MME-EKF-based path-tracking control of autonomous vehicles considering input saturation. IEEE Transactions on Vehicular Technology, 68(6), 5246-5259.
19. Taghavifar, H., & Rakheja, S. (2019). Path-tracking of autonomous vehicles using a novel adaptive robust exponential-like-sliding-mode fuzzy type-2 neural network controller. Mechanical Systems and Signal Processing, 130, 41-55.
20. Hu, C., Gao, H., Guo, J., Taghavifar, H., Qin, Y., Na, J., & Wei, C. (2019). RISE-based integrated motion control of autonomous ground vehicles with asymptotic prescribed performance. ieee transactions on systems, man, and cybernetics: systems, 51(9), 5336-5348.
21. Taghavifar, H., Xu, B., Taghavifar, L., & Qin, Y. (2019). Optimal path-planning of nonholonomic terrain robots for dynamic obstacle avoidance using single-time velocity estimator and reinforcement learning approach. IEEE Access, 7, 159347-159356.
22. Taghavifar, H., & Rakheja, S. (2019). Multi-objective optimal robust seat suspension control of off-road vehicles in the presence of disturbance and parametric uncertainty using metaheuristics. IEEE Transactions on Intelligent Vehicles, 5(3), 372-384.
23. Taghavifar, H., Mardani, A., Hu, C., & Qin, Y. (2019). Adaptive robust nonlinear active suspension control using an observer-based modified sliding mode interval type-2 fuzzy neural network. IEEE Transactions on Intelligent Vehicles, 5(1), 53-62.
24. Wei, C., Romano, R., Merat, N., Wang, Y., Hu, C., Taghavifar, H., & Boer, E. R. (2019). Risk-based autonomous vehicle motion control with considering human driver’s behaviour. Transportation research part C: emerging technologies, 107, 1-14.
25. Taghavifar, H., & Rakheja, S. (2019). Parametric analysis of the potential of energy harvesting from commercial vehicle suspension system. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 233(11), 2687-2700.

Back to top

© Concordia University