| 2009 |
|---|
| 10 | EE | Draguna Vrabie,
O. Pastravanu,
Murad Abu-Khalaf,
Frank L. Lewis:
Adaptive optimal control for continuous-time linear systems based on policy iteration.
Automatica 45(2): 477-484 (2009) |
| 2008 |
|---|
| 9 | EE | Asma Al-Tamimi,
Frank L. Lewis,
Murad Abu-Khalaf:
Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 38(4): 943-949 (2008) |
| 2007 |
|---|
| 8 | EE | Asma Al-Tamimi,
Draguna Vrabie,
Murad Abu-Khalaf,
Frank L. Lewis:
Model-free Approximate Dynamic Programming Schemes for Linear Systems.
IJCNN 2007: 371-378 |
| 7 | EE | Asma Al-Tamimi,
Frank L. Lewis,
Murad Abu-Khalaf:
Model-free Q-learning designs for linear discrete-time zero-sum games with application to H-infinity control.
Automatica 43(3): 473-481 (2007) |
| 6 | EE | Tao Cheng,
Frank L. Lewis,
Murad Abu-Khalaf:
A neural network solution for fixed-final time optimal control of nonlinear systems.
Automatica 43(3): 482-490 (2007) |
| 5 | EE | J. Gadewadikar,
Frank L. Lewis,
L. Xie,
V. Kucera,
Murad Abu-Khalaf:
Parameterization of all stabilizing Hinfinity static state-feedback gains: Application to output-feedback design.
Automatica 43(9): 1597-1604 (2007) |
| 4 | EE | Tao Cheng,
Frank L. Lewis,
Murad Abu-Khalaf:
Fixed-Final-Time-Constrained Optimal Control of Nonlinear Systems Using Neural Network HJB Approach.
IEEE Transactions on Neural Networks 18(6): 1725-1737 (2007) |
| 3 | EE | Asma Al-Tamimi,
Murad Abu-Khalaf,
Frank L. Lewis:
Adaptive Critic Designs for Discrete-Time Zero-Sum Games With Application to Hinfty Control.
IEEE Transactions on Systems, Man, and Cybernetics, Part B 37(1): 240-247 (2007) |
| 2 | EE | Tao Cheng,
Frank L. Lewis,
Murad Abu-Khalaf:
Neural network solution for finite-horizon Hinfinity state feedback control of nonlinear systems.
Int. J. Systems Science 38(12): 1029-1041 (2007) |
| 2005 |
|---|
| 1 | EE | Murad Abu-Khalaf,
Frank L. Lewis:
Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach.
Automatica 41(5): 779-791 (2005) |
