Advanced Controls and Sensors Group

Technical Lead: F.L. Lewis, Ph.D.

National Academy of Inventors
Fellow IEEE, Fellow IFAC,
Fellow U.K. Inst Measurement & Control
Fellow European Union Academy of Science
Professional Engineer, Texas
Chartered Engineer U.K. Eng. Council
University Distinguished Scholar Professor
University Distinguished Teaching Professor
lewis@uta.edu
Moncrief-Donnell Endowed Chair

F.L. Lewis Professional Details

Résumé
- PhD Students
- Patents
- Grants and Contracts
Publication List- Books and Papers
Brief Biosketch

EE "Systems and Controls" Courses and Notes

Research Areas

See recent presentations below

Cooperative Control of Distributed Systems on Graphs
Cooperative control of Renewable Energy Microgrids
Reinforcement Learning & Approximate Dynamic Programming
See recent presentations below
- ADP for discrete time systems
- ADP for continuous-time systems
Human-Robot Interactions
Intelligent Nonlinear Control
Neural network control of robots and nonlinear systems
- Neural network control
- Hamilton Jacobi equation solution using neural networks
- Optimal control for nonlinear systems
- H-infinity (game theory) control
Discrete Event Supervisory Control
- For robotic assembly cells
- For wireless sensor networks
Intelligent Diagnostics and Prognostics

Software from sponsored research

Main Books

F.L. Lewis, D. Vrabie, and V. Syrmos, Optimal Control, third edition, John Wiley and Sons, New York, 2012.

F.L. Lewis, L. Xie, and D. Popa, Optimal & Robust Estimation: With an Introduction to Stochastic Control Theory, CRC Press, Boca Raton, 2007. Second Edition.

B.L. Stevens, F.L. Lewis, E.N. Johnson, Aircraft Control and Simulation: Dynamics, Control, and Autonomous Systems, John Wiley and Sons, New York, Feb. 1992. Third edition 2015. http://www.wiley.com/WileyCDA/WileyTitle/productCd-1118870980.html

D. Vrabie, K. Vamvoudakis, and F.L. Lewis, Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles, IET Press, 2012.

F.L. Lewis and Derong Liu, editors, Reinforcement Learning and Approximate Dynamic Programming for Feedback Control, John Wiley/IEEE Press, Computational Intelligence Series. 2012.

F.L. Lewis, H. Zhang, K. Hengster-Movric, A. Das, Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches, Springer-Verlag, 2014.

F.L. Lewis, S. Jagannathan, and A. Yesildirek, Neural Network Control of Robot Manipulators and Nonlinear Systems, Taylor and Francis, London, 1999. download pdf file

F.L. Lewis, Applied Optimal Control and Estimation: Digital Design and Implementation, Prentice-Hall, New Jersey, TI Series, Feb. 1992. download pdf file

F.L. Lewis, D.M. Dawson, and C.T. Abdallah, Robot Manipulator Control: Theory and Practice, 2nd edition, Revised and Expanded, CRC Press, Boca Raton, 2006. download pdf file

Y. Kim and F.L. Lewis, High-Level Feedback Control with Neural Networks, World Scientific, Singapore, 1998.

G. Vachtsevanos, F.L. Lewis, M. Roemer, A. Hess, B. Wu, Intelligent Fault Diagnosis and Prognosis for Engineering Systems, John Wiley, New York, 2006.

Older Invited Presentations

Students

Information for New Students Applying

Ph.D. Students

Jim Worsham, "Aircraft Autopilot Controller Design," PhD Funded by Lockheed Martin, Sept 2021-present.

Yusuf Kartal, Autonomous Aerial Vehicles Distributed Control and Interactive Games, Department of Electrical Engineering, University of Texas at Arlington, in progress. Sept. 2019 - present.

Bosen Lian, Distributed Estimation and Inverse Reinforcement Learning for Multi-agent Systems, PhD degree, Department of Electrical Engineering, University of Texas at Arlington, in progress. Dec. 2021.

Recent Former Ph.D. Students

Shan Zuo Susan, Distributed Resilient Control Of Multi-Agent Systems With Applications to Microgrids, Lewis is coadviser. Main Adviser is Ali Davoudi.

Victor Lopez, Optimal Control Strategies for Dynamical Multiagent Systems in Graphical Games

Patrik Kolaric, Decision & Reinforcement Learning Control for multi-agent autonomous systems

Bakur ALQaudi- Brain functions, Adaptive Resonance Theory, and Their Use in Decision and Control Systems

Bahare Kiumarsi, reinforcement learning and biologically inspired control

Hamidreza Modares, reinforcement learning for feedback control

Vahidreza Nasirian, Revisiting established control paradigms in emerging energy hubs (Coadvised. Main adviser is Dr. Ali Davoudi, EE, UTA)

Ali Bidram, cooperative control for electric power microgrid (Coadvised. Main adviser is Dr. Ali Davoudi, EE, UTA)

Kristian Hengster-Movric, cooperative control systems, distributed optimal design on graphs

Muhammad Aurangzeb, Coalitions and Games on Graphs

Mohammed Abouheaf, cooperative graphical games, reinforcement learning for power system economic dispatch

Kyriakos Vamvoudakis, neural networks for feedback control

Emanuel Stingu, autonomous aerial vehicles, helicopters

Draguna Vrabie, Neural Networks for Control- Approximate Dynamic Programming for continuous-time systems

Abhijit Das, nonlinear autopilots for UAV helicopters

Prasanna Ballal, Wireless Sensor Networks

Pritpal Dang, Man-Machine Interface

J. Gadewadikar, H-infinity control, output feedback control, helicopter UAV control

Asma AL-Tamimi, Approximate Dynamic Programming for discrete-time systems

Cheng Tao, finite horizon optimal control for nonlinear systems

M. Abu-Khalaf, Nonlinear Control and HJB Equation Design

B. Borovic, Microelectromechanical systems (MEMS)

J. Mireles, Intelligent Robot Control, Microelectromechanical systems (MEMS)

Research Supported by (Past and Present):

National Science Foundation

Office of Naval Research

Army Research Office, Army National Automotive Center, TARDEC/RDECOM

Air Force Office of Scientific Research

ONR, NASA, and ARO SBIR Contracts