Meysar Zeinali-Ghayeshghorshagh

Research

• Object Detection and Tracking for robotic application using Deep-Learning Techniques (Recent)
• Machine Learning-Based Solutions for your industrial systems.
• Robot Learning Control Using Recurrent Neural Network (Deep learning -LSTM) and Adaptive Sliding Mode Control (Recent).
• Path planing and colission avidance algorthm development and impementation  for Autonomous Vehicles based on GPS Data (Recent​)
• Multi-Model Neural Network-Based Robust and Adaptive Control System Development for Robotic Applications. 
• Development of a Vision-Based Robot Learning Control for Assistive Robots: This project is aiming at developing an innovative robot learning and control system that realize and improves human-robot interaction in assistive and collaborative robots, robots motion, object manipulation skills, by perception and adaption to a human environment, by robust and accurate movements, and by making correct decisions in a stochastic and dynamic environment (focusing on learning issues of assistive robots).
• Human and Object Detection, tracking  Using Deep Learning and Using Single Camera:  In this research a novel distance measurement and object identification and feature extraction has been developed using deep-learning techniques and single camera for robotics applications.
• Automated Laser Additive Manufacturing System development (Laser Metal Deposition by Powder Injection): This is a collaborative research between I and the Automated Laser Fabrication Laboratory (ALFa) of the University of Waterloo to develop an intelligent control system which is used to produce near net-shaped parts and repair expensive machine components. Identification and modelling of the process and control of height (thickness) of each deposited layer is an important part of my rsearch.
• High Performance Hydraulics Systems Design and Analysis (Developed a Software): This research targets modeling, simulation and implementation of nonlinear adaptive control for the mechnical and mechatronics systms that use high-performance hydraulic systems for their actuation.

Awards

Teaching

Courses  Develped and Taught:

1. CPSC-5616: Machine Learning and Deep Learning (Offered in Winter 2024)
2. ENGR-5556: Advanced Modelling and Control of Robot Manipulators ( (Offered in Fall 2023)
3. ENGR-5566: Advanced Fluid Power System Modelling and Control
4. ENGR-4576: Digital Logic and Microprocessor
5. ENGR-4547: Introduction to Robot Manipulation
6. ENGR-3547: Control Systems
7. ENGR-4526: Sensors and Instrumentation
8. ENGR-4566: Fluids Power Systems (Hydraulic and Pneumatics)
9. ENGR-2506: Dynamics
10. ENGR-4416: Fluid Particle Technology

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Publications

Selected Publications:

• R Patel, M Zeinali, K Passi, Deep Learning-based Robot Control using Recurrent Neural Networks (LSTM; GRU) and Adaptive Sliding Mode Control, Proceedings of the 8th International Conference on Control, Dynamic Systems, and Robotics, 2021.cdsr.net.
  

• M Arsenault, LF Tremblay, M Zeinali, Optimization of trajectory durations based on flow rate scaling for a 4-DoF semi-automated hydraulic rockreaker, Internation Journal of Mechanism and Machine Theory 143, 103632, 2020.
  

• M Zeinali, H Wang, New Methodology to Design Learning Control for Robots Using Adaptive Sliding Mode Control and Multi-Model Neural Networks, Proceedings of the 5th International Conference on Control, Dynamic Systems, and Robotics, 2018.
  
• Zeinali, M., and Notash, L., Adaptive sliding mode control with uncertainty estimator for robot manipulators, Journal of Mechanism and Machine Theory, Vol. 45, No. 1, pp. 80-90, 2010.  [This paper ranked 4 and 7 among top 25 most read articles in the Journal During  September 2009- September 2010].
  
• Zeinali, M., Multi-Layer Fuzzy System Modeling a New Approach: Theory and Application, Proc. of  International Conference on Fuzzy Theory and Its Applications (iFUZZY 2017),  Kenting, TAIWAN, Nov. 12-15, 6-Pages, 2017 [Best Paper Competition Finalist].
  
• M Zeinali, First-Order Continuous Adaptive Sliding Mode Control for Robot Manipulators with Finite-Time Convergence of Trajectories to Real Sliding Mode, 15th International Workshop on Variable Structure Systems (VSS), 261-266, 2018.                
  
• Louis-Francis Tremblay, Marc Arsenault, M Zeinali, Development of a trajectory planning algorithm for a 4-DoF rockbreaker based on hydraulic flow rate limits,Transactions of the Canadian Society for Mechanical Engineering 173, 2019.​​
• Kunwar, S., and Zeinali, M., Human Head and Face Detection Using Single Camera to Improve Human Robot Interaction, Proc. of 25th CANCAM London, Canada, May 31-June 4, 2015.
• Zeinali, M., Sliding Mode Control Design for Robot Manipulators Based on Online Estimation of Uncertainties and Its Experimental Verification, Journal of Mechatronics, doi: 10.1166/jom. 2015.1095, Vol.3(2), pp. 85-97, 2015.
• Zeinali, M., A Novel Approach to Build a Learning Controller by Combining Fuzzy Modeling, Sliding Mode, and PID Control for Robotic Applications, ASME 2013 Conference on Information Storage and Processing Systems, Pages V001T07A009, California, Santa Clara, June 24, 2013.
• Farshidianfar M., Khajepour A., Gerlich A., and Zeinali M., System Identification and Height Control of Laser Cladding Using Adaptive Neuro-Fuzzy Inference Systems, ICALEO 32th Int. Conf. on, Application of Lasers and Electro-Optics, Florida, USA, October 2013.
• Alizadeh, P., Zeinali M., "A Real-Time Object Distance Measurement Using a Monocular Camera" Proceedings of 24th IASTED international Conference on Modelling and Simulation, Canada, Alberta, Banff, July 17, 2013.
• Fazeli, A., Zeinali, M., and Khajepour, A., Application of Adaptive Sliding Mode Control for Regenerative Braking Torque Control of Air-Hybrid Engine, IEEE/ASME TRANSACTIONS ON MECHATRONICS, DOI: 10.1109/TMECH.2011.2129525, Issue 99, pp.745-755, 2012.
• Zeinali, M., Learning Controller Design using Fuzzy Modeling, Sliding Mode Control, and PID controller for Robots, The 14th IASTED International Symposium on International Symposium on Intelligent Systems and Control, pp. 287-292, 2013.
• Zeinali, M., and Khajepour, A., Height Control in Laser Cladding Using Adaptive Sliding Mode Technique: Theory and Experiment, ASME Journal of Manufacturing Science and Engineering, Vol. 132, Issue 4, 10pages, 2010.
• Zeinali, M., and Khajepour, A., Development of an Adaptive Fuzzy Logic-Based Inverse Dynamic Model for Laser Cladding Process, Journal of Engineering Application of Artificial intelligence, No 23, pp.1408–1419, 2010
• Fazeli A., Zeinali M., Khajepour A., Pournazeri M. "Air Hybrid Engine Torque Control Using Adaptive Sliding Mode Control" ASME International Mechanical Engineering Congress and Exposition IMECE2010, November 12-18, 2010, Vancouver, British Columbia, Canada, 2010.
• Zeinali, M., and Khajepour, A., Design and Application of Robust Adaptive Controller to Cable-Driven Parallel Robot Manipulator: Theory and Experiment, ASME 2010 Int. Design Engineering Technical Conf. and Computers and Information in Engineering, Montreal, Quebec, Canada, August 15-18, 2010.
• Zeinali, M., and Khajepour, A., Adaptive Fuzzy Sliding Mode Control Design and Application to Laser Metal Deposition, Proc. Of American Control Conference ACC2010, Baltimore, Maryland, USA, June 30-July 02, 2010.