National Science Foundation
Army Research Office, National Automotive Center, TARDEC
US Air Force Office of Scientific Research, Office of Naval Research
This software is not supported. If you have trouble making it work, please figure it out yourself. The methods are explained in the papers.
Bidram, A.; Davoudi, A.; Lewis, F.L., “A Multiobjective Distributed Control Framework for Islanded AC Microgrids,” IEEE Trans. Industrial Informatics, Volume 10, no. 3, Pages: 1785 – 1798, 2014.
Ling-ling Fan, V. Nasirian, H. Modares, F.L. Lewis, Y.D. Song, and A. Davoudi, “Game-theoretic Control of Active Loads in DC Microgrids,” IEEE Trans. Energy Conversion, vol. 31, no. 3, pp. 882-895, 2016.
V. Nasirian, H. Modares, F. Lewis, and A. Davoudi, "Active loads of a microgrid as players in a differential game," Proc. IEEE 7th International Symposium on Resilient Control Systems, Paper ID: ID-000388, Aug. 2015
K.G. Vamvoudakis, F.L. Lewis, and G.R. Hudas, “Multi-Agent Differential Graphical Games: online adaptive learning solution for synchronization with optimality,” Automatica, vol. 48, no. 8, pp. 1598-1611, Aug. 2012.
M. Abouheaf, K. Vamvoudakis, S. Haesaert, F. Lewis, and R. Babuska, “Multi-Agent Discrete-Time Graphical Games and Reinforcement Learning Solutions,” Automatica, Vol. 50(12), pp. 3038-3053, 2014.
M. Abouheaf, F. Lewis, M. Mahmoud, and D. Mikulski, “Discrete-Time Dynamic Graphical Games: Model-Free Reinforcement Learning Solution,” Control Theory and Technology, vol. 13(1), pp. 333-347, 2015.
 L. Zhu, H. Modares, Gan Oon Peen, F.L. Lewis, and Baozeng Yue, “Adaptive Suboptimal Output-Feedback Control for Linear Systems Using Integral Reinforcement Learning,” IEEE Trans. Control Systems Technology, vol. 23, no. 1, pp. 264-273, Jan. 2015.
AD HDP (Q learning)
 A. Al-Tamimi, M. Abu-Khalaf, and F.L. Lewis, “Adaptive Critic Designs for Discrete-Time Zero-Sum Games with Application to H-Infinity Control,” IEEE Trans. Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 37, no. 1, pp. 240-247, Feb. 2007.
A. Al-Tamimi, F.L. Lewis, and
M. Abu-Khalaf, “Model-free Q-learning designs for linear discrete-time zero-
 B. Kiumarsi, F.L. Lewis, H. Modares, and M.B. Naghibi-Sistani, “Reinforcement Q-Learning for Optimal Tracking Control of Linear Discrete-time Systems with Unknown Dynamics,” Automatica, vol. 50, pp. 1167-1175, 2014.
 D. Vrabie, O. Pastravanu, M. Abu-Khalaf, and F. L. Lewis, “Adaptive optimal control for continuous-time linear systems based on policy iteration,” Automatica, vol. 45, pp. 477-484, 2009.
D. Vrabie and F.L. Lewis
H. Modares and F.L. Lewis, “Linear Quadratic Tracking Control of Partially-Unknown Continuous-time Systems using Reinforcement Learning,” IEEE Trans. Automatic Control, vol. 59, no. 11, pp. 3051-3068, Nov. 2014.
H. Modares, F.L. Lewis, and Z.-P. Jiang, “H-infinity Tracking Control of Completely-unknown Continuous-time Systems via Off-policy Reinforcement Learning ,” IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 10, pp. 2550-2562, Oct. 2015.
F.L. Lewis and K.G. Vamvoudakis, “Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data,” IEEE Trans. Systems, Man, And Cybernetics- Part B: vol. 41, no. 1, pp. 14-25, Feb. 2011.
K. Vamvoudakis, D. Vrabie, and F. Lewis, “Online policy
iteration based algorithms to solve the continuous-time infinite horizon
optimal control problem, “Proc. IEEE Symp. ADPRL, pp.
 K.G. Vamvoudakis and F. L. Lewis, “Online Actor Critic Algorithm to Solve the Continuous-Time Infinite Horizon Optimal Control Problem,” Proc. Int. Joint Conf. on Neural Networks, pp. 3180-3187, Atlanta, June 2009.
 F.L. Lewis, K. Liu, and A. Yesildirek, “Neural net robot controller with guaranteed tracking performance,” IEEE Trans. Neural Networks, vol. 6, no. 3, pp. 703-715, 1995.
 F.L. Lewis, A. Yesildirek, and K. Liu, “Multilayer neural net robot controller with guaranteed tracking performance, IEEE Trans. Neural Networks, vol. 7, no. 2, pp. 388-399, Mar. 1996.
 M. Abu-Khalaf, J. Huang, and F.L. Lewis, Nonlinear H2/H-Infinity Constrained Feedback Control: A Practical Design Approach Using Neural Networks, Springer-Verlag, Berlin, 2006.
 M. Abu-Khalaf and F.L. Lewis, “Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach,” Automatica, vol. 41, pp. 779-791, 2005.
 M. Abu-Khalaf, F.L. Lewis, and J. Huang, “Neurodynamic Programming and Zero-Sum Games for Constrained Control Systems,” IEEE Trans. Neural Networks, vol. 19, no. 7, pp. 1243-1252, July 2008.
 J. Gadewadikar, Frank L. Lewis, L. Xie, V. Kucera and M. Abu-Khalaf, “Parameterization of all stabilizing H∞ static state-feedback gains: Application to output-feedback design,” Automatica, vol. 43, no. 9, pp. 1597-1604, September 2007.
 J. Gadewadikar; F.L. Lewis; K. Subbarao; B. M. Chen, “Structured H-Infinity Command and Control-Loop Design for Unmanned Helicopters,” J. Guidance, Control, and Dynamics, vol.31, no.4 , pp. 1093-1102, 2008.
 A. Das, F.L. Lewis, and K. Subbarao, “Backstepping approach for controlling a quadrotor using Lagrangian form dynamics,” J. Intelligent & Robotic Systems, vol. 56, no. 1-2, pp. 127-152, Sept. 2009.
 D. Tacconi and F.L. Lewis, “A new matrix model for discrete event systems: application to simulation,” IEEE Control Systems Magazine, pp. 62-71, Oct. 1997.
 J. Mireles and F.L. Lewis, “Intelligent Material Handling: Development and implementation of a matrix-based discrete-event controller,” IEEE Trans. Industrial Electronics, vol. 48, no. 6, pp. 1087-1097, Dec. 2001.
 V. Giordano, P.Ballal, F.L. Lewis, B. Turchiano, J.B. Zhang, “Supervisory control of mobile sensor networks: matrix formulation, simulation and implementation,” IEEE Trans. Systems, Man, Cybernetics- Part B, vol. 36, no. 4, pp. 806-819, Aug. 2006.
 P. Ballal and F.L. Lewis, “Deadlock free dynamic resource assignment in multi-robot systems with multiple missions: Application in Wireless Sensor Networks”, J. Control Theory and Applications, 2009, to appear.