Mohammed Abouheaf, Ph.D.

Mohammed Abouheaf, Ph.D.

  • Position: Associate Professor
  • Phone: 419-372-3618
  • Email: mabouhe@bgsu.edu
  • Address: 211 Technology Building

Multidisciplinary research and development of multi-scale systems driven by digital manufacturing revolution to help advance industry and service applications.

Robotics Research

Dr. Abouheaf earned his B.Sc. and M.Sc. degrees in Electronics and Communication Engineering from Mansoura University and completed his Ph.D. in Electrical Engineering at the University of Texas at Arlington in 2013. Currently, he holds the position of Associate Professor in the School of Engineering at Bowling Green State University, where he is recognized as one of the founders of the Robotics Engineering program. Dr. Abouheaf's research pursuits encompass a broad spectrum, including Systems & Control, Machine Learning, and Applied Mathematics, all with a specialized focus on the application of autonomous and intelligent systems. His contributions lie in advancing the comprehension, design, and efficacy of cooperative and model reference adaptive control solutions. This is primarily achieved through the utilization of data-driven methodologies, optimization paradigms, and reinforcement learning algorithms.

Education

  • Ph.D., 2013, Electrical Engineering, University of Texas at Arlington, Arlington, Texas Ph.D. Thesis Advisor: Prof. Frank Lewis
  • M.Sc., 2006, Electronics and Communication Engineering, Mansoura University, Mansoura, Egypt
  • B.Sc., 2001, Electronics and Communication Engineering, Mansoura University, Mansoura, Egypt

Academic Positions

  • Associate Professor, Bowling Green State University, School of Engineering, Bowling Green, Ohio (2021-Present)
  • Senior Research Associate, University of Ottawa, School of Electrical Engineering and Computer Science, Ottawa, Ontario, Canada (2017-2021)
  • Postdoctoral Fellow, University of Montreal, Polytechnique Montreal, Institute for Data Valorization (IVADO), Montreal, Quebec, Canada (2016-2017)
  • Assistant Professor, King Fahd University of Petroleum and Minerals, Systems Engineering, Dhahran, Eastern Province, Saudi Arabia (2013-2016)

Research Focus
Research Interests: Systems and Control, Applied Mathematics, and Machine Learning

  • Intelligent and Adaptive Control Systems
  • Optimal and Nonlinear Control Systems
  • Game Theoretic Approaches for Cyber-Physical Systems
  • Mean-Field Approaches for Swarms
  • Non-Convex Optimization
  • Data-Driven Reinforcement Learning Approaches
  • Self-Tuning Regulators and Model-Reference Adaptive Systems
  • Robotic and Unmanned Vehicle Control
  • Effective Smart Grid Integration and Energy Management

Affiliations

  • Autonomous and Intelligent Systems Laboratory (AISL), Bowling Green State University, Director

Funding and Grants Activities (BGSU)

  • (NSF) (Co-PI): Div of Engineering Education and Centers, RET Site: Mission Rebuild Workforce through Advanced Manufacturing Training of K-14 Educators, $ 620,000, 2022-2025. (Award Number–2206952)
  • (NSF)(Co-PI): Div of Engineering Education and Centers, Cultivating Learners’ Autonomy to Improve Math Skills for STEM Learning, $ 298,005, 2022-2025. (Award Number–2142608)
  • (Ohio Department of Higher Education, Regional Training Hub, Regionally Aligned Priorities in Delivering Skills Program RAPIDS) (Co-PI): Advanced Additive Manufacturing: Destructive and Non-destructive Material Testing and Training ($ 150,555).
  • (Ohio Department of Higher Education-- Super RAPIDS) (Co-PI): Next-Gen Engineering Excellence: Aligning Advanced Manufacturing Facilities with Future Skill Priorities in Ohio ($ 764,460.27).
Publications | Book Chapters | Technical Report | Conference Proceedings

Journal Publications

  1. [JN] Abouheaf, M., Lewis, F., Mahmoud, M., and Mikulski, D. (2016) Discrete-Time Dynamic Graphical Games: Model-Free Reinforcement Learning Solution. Control Theory and Technology, 13(1), 55-69. (Best Paper Award)
  2. [JN] Abouheaf, M., Mayyas, M., Hashim, H., and Vamvoudakis, K. (2023) An Online Model-Following Projection Mechanism Using Reinforcement Learning. (IEEE Transactions on Automatic Control-Technical Note) (DOI: 10.1109/TAC.2023.3243165).
  3. [JN] Abouheaf, M., Boase, D., Gueaieb, W., and Spinello, D. (2023) Real-Time Measurement- Driven Reinforcement Learning Control Approach for Uncertain Nonlinear Systems. (Engineer- ing Applications of Artificial Intelligence),https://doi.org/10.1016/j.engappai.2023.106029.
  4. [JN] Abouheaf, M., Vamvoudakis, K., Haesaert, S., Lewis, F., and Babuska, R. (2014) Multi- Agent Discrete-Time Graphical Games and Reinforcement Learning Solutions. Automatica, 50(12), 3038-3053.
  5. [JN] Abouheaf, M. Mailhot, N., Gueaieb, W., and Spinello, D. (2020) Guidance Mechanism for Flexible Wing Aircraft Using Measurement-Interfaced Machine Learning Platform. IEEE Transactions on Instrumentation and Measurements, 69(7), 4637-4648.
  6. [JN] Abouheaf, M., Mahmoud, M., and Gueaieb, W. (2020) Integral Reinforcement Learning Solutions for a Synchronisation System with Constrained Policies. IET Control Theory & Applications. 14(12), 1599-1611.
  7. [JN] Abouheaf, M., Gueaieb, W., and Lewis, F. (2019) Online Model-Free Reinforcement Learning for the Automatic Control of a Flexible Wing Aircraft. IET Control Theory & Applications, 14(1), 73-84.
  8. [JN] Hashim, H., Abouheaf, M., Abido, M., (2021) Geometric Stochastic Filter With Guaranteed Performance for Autonomous Navigation Based on IMU and Feature Sensor Fusion, Control Engineering Practice, 116, 2021, 104926. Featured by the Journal of Control Engineering Practice (September, 2022). Featured by Elsevier Computer Science Journals & Books Leading up to the IEEE CDC 22 (December, 2022).
  9. [JN] Hashim, H., Abouheaf, M., and Vamvoudakis, K. (2021) Neuro-Adaptive Stochastic Attitude Filter on SO(3). IEEE Control Systems Letters, doi: 10.1109/LCSYS.2021.3123227. (Accepted for Publication in ACC-2022).
  10. [JN] Abouheaf, M., Qu, S., Gueaieb, W., Abielmona, R., and Harb, M. (2020) Responding to Illegal Activities Along the Canadian Coastlines Using Reinforcement Learning. IEEE Instrumentation and Measurement Magazine, Magazine, 24(2), 118-126.
  11. [JN] Nahas, N., Abouheaf, M., Gueaieb, W, and Sharaf A. (2019) A Self-Adjusting Adaptive AVR-LFC Scheme for Synchronous Generators. IEEE Transactions on Power Systems, DOI:10.1109/TPWRS.2019.2920782.
  12. [JN] Mahmoud, M., Alyazidi, N., and Abouheaf, M. (2018) Adaptive Critics Based Cooperative Control Scheme for Islanded Microgrids. Neurocomputing, (272), 532-541.
  13. [JN] Abouheaf, M., Gueaieb, W., and Sharaf, A. (2019) Load Frequency Regulation for Multi- Area Power System Using Integral Reinforcement Learning. IET Generation, Transmission & Distribution. 13(19), 4311-4323.
  14. [JN] Abouheaf, M., Lee, W. J., and Lewis, F. (2013) Dynamic Formulation and Approxi- mation Methods to Solve Economic Dispatch Problems. IET Generation, Transmission, & Distribution, 7(8), 866-873.
  15. [JN] Abouheaf, M., Gueaieb, W., and Sharaf A. (2018) Model-Free Adaptive Learning Control Scheme for Wind Turbines with Doubly-Fed Induction Generators. IET Renewable Power Generation, 12(14), 1675-1686.
  16. [JN] Nahas, N., Abouheaf, M., and Sharaf, A. (2021) A Multi-Objective AVR-LFC Opti- mization Scheme for Multi-Area Power Systems. Electric Power Systems Research, 200, 107467.
  17. [JN] Kouritem, S., Abouheaf, M., Nahas, N., Hassan, M. (2022) A Multi-Objective Op- timization Design of Industrial Robot Arms. Alexandria Engineering Journal, 61 (12), 12847-12867.
  18. [JN] Nahas, N., Nourelfath, N., and Abouheaf, M., (2022) Optimized Buffer Allocation and Repair Strategies for Series Production Lines. (Journal of Industrial and Production Engineering) (http://doi.org/10.24867/IJIEM-2022-4-316).
  19. [JN] Wang, N.,Abouheaf, M. and Gueaieb, W. (2020) Model-Free Optimized Tracking Control Heuristic. Robotics, 9(3), 49.
  20. [JN] Abouheaf, M. Gueaieb, W, and Spinello, D. (2019) Online Multi-Objective Model- Independent Adaptive Tracking Mechanism for Dynamical Systems. Robotics, 8(4), 82.
  21. [JN] Abouheaf, M., Gueaieb, W., and Lewis, F. (2018) Model-Free Gradient-Based Adaptive Learning Controller for an Unmanned Flexible Wing Aircraft. Robotics, 7, 66.
  22. [JN] Abouheaf, M. and Gueaieb, W. (2019) Online Model-Free Controller for Flexible Wing Aircraft: A Policy Iteration-Based Reinforcement Learning Approach. International Journal of Intelligent Robotics & Applications, 4, 21-43.
  23. [JN] Mahmoud, M., Alyazidi, N., and Abouheaf, M. (2017) Adaptive Intelligent Techniques For Microgrid Control Systems: A Survey. Int. Jr. of Elect. Pwr. Eng. Sys., 90, 292-305.
  24. [JN] Abouheaf, M., Mahmoud, M., and Hussain, S. (2015) A Novel Approach to Control of Autonomous Microgrid Systems. Int. Journal of Energy Engineering. 5(5), 125-136.
  25. [JN] Nahas, N., Abouheaf, M., Sharaf A., and Gueaieb, W. (2018) Iterated Local Search Solution for the Non-Convex Economic Dispatch Problem. International Journal of Modeling and Optimization. 8(6), 326-333.
  26. [JN] Mahmoud, M., Abouheaf, M. and Sharaf, A. (2019) Reinforcement learning control approach for autonomous microgrids. International Journal of Modelling and Simulation. DOI: 10.1080/02286203.2019.1655701
  27. [JN] Abouheaf, M., Haesart, S., Lee, W., and Lewis, F. (2012) Q-Learning with Eligibility Traces to Solve Non-Convex Economic Dispatch Problems. International Journal of Electrical Science and Engineering, 7(7), 1390-1396.
  28. [JN] Nahas, N., Dargouth, M., and Abouheaf, M. (2019) A NonLinear Threshold Accepting Function Based Algorithm for the Solution of Economic Dispatch Problem. RAIRO-Operations Research. 54(5), 1269-1289.
  29. [JN] Abouheaf, M. and Mahmoud, M. (2017) Policy Iteration and Coupled Riccati Solutions for Dynamic Graphical Games. International Journal of Digital Signals & Smart Systems, 1(2), 143-162.
  30. [JN] Abouheaf, M., Gueaieb, W., and Samrah, A. (2018) Modeling of Evanescent-Wave Coupling Between Optical Dielectric Waveguides. International Journal of Modelling and Simulation. 39(1), 38-47.

Book Chapters

  1. [BC] Abouheaf, M. and Mahmoud M. (2016) Book Title: Microgrid: Advanced Control Methods and Renewable Energy System Integration. Chapter 5: Online Adaptive Learning Control Schemes for Microgrids. Oxford : Butterworth-Heinemann, 137-171.
  2. [BC] Abouheaf, M., Gueaieb, W., Lewis, F., and Sharaf, A. (2019) Book Title: Medium Voltage Direct Current Grid: Resilient Operation, Control and Protection. Chapter 5: An Adaptive Learning Flexible Control Scheme for Wind Doubly-Fed Induction Generator. Elsevier Academic Press, 101-126.
  3. [BC] Alyazidi, N., Abouheaf, M., Mahmoud, M., and Sharaf, A. (2019) Book Title: Vol No. 2, New Trends in Observer-based Control: A Practical Guide to Process and Engineering Applications. Chapter 3: Stochastic Control Approach for Distributed Generation Units Interacting on Graphs. Elsevier Academic Press. 77-98.
  4. [BC] Nahas, N., Abouheaf, M., and Sharaf, A. (2019) Book Title: Sustainable Energy Technologies and Systems. Chapter 5: Non-Convex Economic Dispatch Solution Using Modified Fast Search. Lambert Academic Publishing, 117-135.
  5. [BC] Abouheaf, M., Gueaieb, W., Sharaf, A., and Lewis, F. (2019) Book Title: Sustainable Energy Technologies and Systems. Chapter 11: Innovative Machine Learning Approaches for Load Frequency Regulation. Lambert Academic Publishing, 257-280.
  6. [BC] Abouheaf, M. and Lewis, F. (2014) Book Title: Frontiers Of Intelligent Control and Information Processing. Chapter 1: Dynamic Graphical Games: Online Adaptive Learning Solutions Using Approximate Dynamic Programming. World Scientific Publishing, 1-48.

Technical Report

  1. [TN] Abielmona, R., and Abouheaf, M. (2020) Realizing situational awareness in information domain: literature search on streaming information. Defence Research Reports, 1-91.

Conference Proceedings

  1. [CN] Qu, S., Abouheaf, M., Gueaieb, W. and Spinello, D. (2021) An Adaptive Fuzzy Reinforcement Learning Cooperative Approach for the Autonomous Control of Flock Systems. (ICRA21: Int. Conf. on Robot. & Autom.) Xi’an, China.
  2. [CN] Abouheaf, M. and Gueaieb, W. (2019) Multi-Agent Synchronization Using Online Model-Free Action Dependent Dual Heuristic Dynamic Programming Approach. (ICRA19: Int. Conf. on Robot. & Autom.) Montreal, Canada.
  3. [CN] Abouheaf, M. and Lewis, F. (2018) Action Dependent Dual Heuristic Dynamic Program- ming Solution for the Dynamic Graphical Games. (CDC18: 57th Conference on Decision and Control) Miami Beach, FL, USA.
  4. [CN] Abouheaf, M., Lewis, F., and Mahmoud, M. (2014) Model-Free Adaptive Learning Solutions for Discrete-Time Dynamic Graphical Games. (CDC14: 53rd IEEE Conference on Decision and Control) California, USA.
  5. [CN] Abouheaf, M. and Lewis F., (2013) Multi-Agent Differential Graphical Games: Nash Online Adaptive Learning Solutions. (CDC13: 52nd IEEE Conference on Decision and Control) Florence, Italy.
  6. [CN] Abouheaf, M., Mahmoud, M., and Lewis, F. (2019) Policy Iteration Solution for Differ- ential Games with Constrained Control Policies. (ACC19: American Control Conference) Philadelphia, PA, USA.
  7. [CN] Abouheaf, M., Lewis, F., Haesart, S., Babsuka, R., and Vamvoudakis, K. (2013) Multi-Agent Discrete-Time Graphical Games: Interactive Nash Equilibrium and Value Iteration Solution. (ACC13: American Control Conference) Washington, DC, USA.
  8. [CN] Abouheaf, M., Lewis, F., and Mahmoud, M. (2014) Differential Graphical Games: Policy Iteration Solutions and Coupled Riccati Formulation. (ECC14: 13th European Control Conf.) Strasbourg, France.
  9. [CN] Abouheaf, M., Suruz, M., Gueaieb, W., and Spinello, D. (2020) Trajectory Tracking of Underactuated Sea Vessels With Uncertain Dynamics: An Integral Reinforcement Learning Approach. (SMC20: IEEE Int. Conf. on Sys., Man, and Cyb.) Toronto, Canada.
  10. [CN] Wang, N., Abouheaf, M., and Gueaieb, W. (2020) Data-Driven Optimized Tracking Control Heuristic for MIMO Structures: A Balance System Case Study. (SMC20: IEEE Int. Conf. on Sys., Man, and Cyb.) Toronto, Canada.
  11. [CN] Abouheaf, M. and Lewis, F. (2013) Approximate Dynamic Programming Solutions of Multi-Agent Graphical Games Using Actor-Critic Network Structures. (IJCNN13: Intern. Joint Conf. on Neural Networks) Dallas, USA.
  12. [CN] Najum, I., Nahas, N., and Abouheaf, M., (2023) Optimisation d’une chaîne d’approvisionnement à plusieurs fournisseurs et plusieurs client.CIGI QUALITA MOSIM 2023 (Congrès CIGI Qualita MOSIM 2023 · Propulser la performance).
  13. [CN] Gao, F., Lower, V., Abouheaf, M., Krishnankuttyrema,R., and Sarder, M. (2023) Design- ing a Student-Facing Learning Analytics Dashboard to Support Online STEM Practices.(LAK23: 13th International Learning Analytics and Knowledge Conference).
  14. [CN] Bani-Hani, M., Kouritem, S., Nahas, N., Abouheaf, M., and Ayman, Y. (2023) Earthquake-Induced Structural Vibration Sensing Device.(13th IEEE International Conference on Power, Energy and Electrical Engineering (CPEEE 2023)).
  15. [CN] Kouritem, S., Altabey, W., Nahas, N., and Abouheaf, M., (2022) New Design of Minimized Torque and Actuators for Industrial Robot Arms, (International Conference on Electrical, Computer, Communications and Mechatronics Engineering).
  16. [CN] Kouritem, S., Altabey, W., Nahas, N., and Abouheaf, M., (2022) Simplified Torque Mod- eling for Different Planer Robots Sizes, (International Conference on Electrical, Computer, Communications and Mechatronics Engineering).
  17. [CN] Altabey, W., Kouritem, S., Abouheaf, M., and Nahas, N., (2022) A Deep Learning- Based Approach for Pipeline Cracks Monitoring, (International Conference on Electrical, Computer, Communications and Mechatronics Engineering).
  18. [CN] Altabey, W., Kouritem, S., Abouheaf, M., and Nahas, N., (2022) Research in Image Processing for Pipeline Crack Detection Applications, (International Conference on Electrical, Computer, Communications and Mechatronics Engineering).
  19. [CN] Abouheaf, M., Gueaieb, W., Spinello, D., and Al-Sharhan, S. (2021) A Data-Driven Model-Reference Adaptive Control Approach Based on Reinforcement Learning. (ROSE2021: 14th IEEE International Symposium on Robotic and Sensors Environments), Ottawa, Canada.
  20. [CN] Qu, S., Abouheaf, M., Gueaieb, W., and Spinello, D. (2021) A Policy Iteration Approach for Flock Motion Control. (ROSE2021: 14th IEEE International Symposium on Robotic and Sensors Environments), Ottawa, Canada.
  21. [CN] Suruz, M., Elhussein, A., Keshtkar, F., and Abouheaf, M., (2020) Model-free Reinforce- ment Learning Approach for Leader-Follower Formation using Nonholonomic Mobile Robots. (FLAIRS20: 33rd International Florida Artificial Intelligence Research Society Conf.) North Miami Beach, Florida, USA
  22. [CN] Abouheaf, M. and Gueaieb, W. (2019) Model-Free Adaptive Control Approach Using Integral Reinforcement Learning. (ROSE19: IEEE Int. Sym. on ROb. and SEns. Env.) Ottawa, Canada.
  23. [CN] Abouheaf, M. and Gueaieb, W.(2019) An Online Reinforcement Learning Wing-Tracking Mechanism for Flexible Wing Aircraft. (ROSE19: IEEE Int. Sym. on ROb. and SEns. Env.) Ottawa, Canada.
  24. [CN] Abouheaf, M. and Gueaieb, W. (2019) Neurofuzzy Reinforcement Learning Control Schemes for Optimized Dynamical Performance. (ROSE19: IEEE Int. Sym. on ROb. and SEns. Env.) Ottawa, Canada.
  25. [CN] Abouheaf, M. and Gueaieb, W. (2018) Reinforcement Learning Solution with Costate Approximation for Flexible Wing Aircraft. (CIVEMSA18) Ottawa, Canada.
  26. [CN] Abouheaf, M. and Gueaieb, W. (2018) Model-Free Value Iteration Solution for The Dynamic Graphical Games. (CIVEMSA18) Ottawa, Canada.
  27. [CN] Abouheaf, M. and Gueaieb, W. (2017) Multi-Agent Reinforcement Learning Approach Based on Reduced Value Function Approximations. (IRIS17: 5th International Symposium on Robotics and Intelligent Sensors) Ottawa, Canada.
  28. [CN] Abouheaf, M. and Gueaieb, W. (2017) Flocking Motion Control for a System of Nonholonomic Vehicles. (IRIS17: 5th International Symposium on Robotics and Intelligent Sensors) Ottawa, Canada.
  29. [CN] Abouheaf, M. and Mahmoud M. (2016) Online Policy Iteration Solution for Dynamic Graphical Games. (SSD16: 23th International Multi-Conference on Systems, Signals and Devices) Leipzig, Germany.
  30. [CN] Abouheaf, M., Haesart, S., Lee, W., and Lewis, F. (2014) Approximate and Reinforce- ment Learning Techniques to Solve Non-Convex Economic Dispatch Problems. (SSD16: 11th International Multi-Conference on Systems, Signals & Devices) Barcelona, Spain.
  31. [CN] Binetti, G., Abouheaf, M., Lewis, F., Davoudi, A., and Turchiano, B. (2013) Distributed Solution for the Economic Dispatch Problem. (MED13: 21st Mediterranean Conference on Control & Automation) Crete, Greece.
  32. [CN] Nahas, N. and Abouheaf, M. (2016) Novel Heuristic Solution for the Non-Convex Economic Dispatch Problem. (SSD16: 23th International Multi-Conference on Systems, Signals and Devices), Leipzig, Germany.
  33. [CN] Gomaa, R., Samraa, A., and Abouheaf, M. (2006) Evanescent Wave Coupling Between Optical Fiber and Planar Optical Waveguide. 23rd National Radio Conference NRSC Menoufiya, Egypt.

Updated: 07/01/2024 12:34PM