Links

Publications



Selected Journal Publications:

  • Behzad Farzanegan, R. Moghadam, S. Jagannathan and Pappa Natarajan, Optimal Adaptive Tracking Control of Partially Uncertain Nonlinear Discrete-Time Systems Using Lifelong Hybrid Learning, in IEEE Transactions on Neural Network and Learning Systems, pp. 1-12, August 2023, doi: 10.1109/TNNLS.2023.3301383.
  • R. Moghadam, V. Narayanan and S. Jagannathan, Event-triggered Optimal Adaptive Control of Partially Unknown Linear Continuous-time Systems with State Delay, in IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 53, no. 6, pp. 3324-3337, June 2023, doi: 10.1109/TSMC.2022.3223986.
  • R. Moghadam and S. Jagannathan, Optimal Adaptive Control of Uncertain Nonlinear Continuous-time Systems with Input and State Delays, in IEEE Transactions on Neural Network and Learning Systems, vol. 34, no. 6, pp. 3195-3204, June 2023, doi: 10.1109/TNNLS.2021.3112566.
  • R. Moghadam, P. Natarajan and S. Jagannathan, Online Optimal Adaptive Control of Partially Uncertain Nonlinear Discrete-time Systems using Multilayer Neural Networks, IEEE Transactions on Neural Network and Learning Systems,  vol. 33, no. 9, pp. 4840-4850, Sept. 2022, doi: 10.1109/TNNLS.2021.3061414.
  • A. Musfata, H. Modares and R. Moghadam, Resilient Synchronization of Distributed Multi-agent Systems under Attacks, in Automatica, vol. 115,  108869, May 2020.
  • R. Moghadam, S. Jagannathan, V. Narayanan and K. Raghavan, Optimal Adaptive Control of Partially Uncertain Linear Continuous-time Systems with State Delay, in Handbook of Reinforcement Learning and Control. pp. 243-272, Cham: Springer International Publishing, 2021.
  • R. Moghadam and H. Modaress, Resilient Autonomous Control of Distributed Multi-agent Systems in Contested Environments, in IEEE Transaction on Cybernetics, vol. 49, no. 11, pp. 3957-3967, Nov. 2019, doi: 10.1109/TCYB.2018.2856089.
  • P. Natarajan, R. Moghadam and S. Jagannathan, Online Deep Neural Network-based Feedback Control of a Lutein Bioprocess, in Journal of Process Control, vol. 98, pp. 41-51, Feb. 2021.
  • R. Moghadam and H. Modares, Resilient Adaptive Optimal control of Distributed Multi-agent Systems Using Reinforcement Learning, IET Control Theory & Applications, vol. 12, no. 16, pp. 2165-2174, Nov. 2018. 
  • R. Moghadam and F.L. Lewis, Output-Feedback H∞ Quadratic Tracking Control of Linear Systems Using Reinforcement Learning, International Journal of Adaptive Control and Signal Processing, vol. 33, pp. 300-314, 2019.
  • H. Modares, R. Moghadam, F. L. Lewis, and A. Davoudi, Static Output-feedback Synchronization of Multi-agent Systems: A Secure and Unified Approach, IET Control Theory & Applications, vol. 12, no. 8, pp. 1095-1106, 2018.

Selected Conference Publications:

  • R. Moghadam and Arman Sharifi, 2023, Lyapunov-Based IMP Attack Analysis on Distributed Multi-Agent Systems, Accepted in IEEE Conference on Systems, Man, and Cybernetics (SMC), Hawaii, USA.
  • R. Moghadam, B. Farzanegan and S. Jagannathan, 2022, Optimal Adaptive Output Regulation of Uncertain Nonlinear Discrete-time Systems using Lifelong Concurrent Learning, 61th IEEE Conference on Decision and Control (CDC), Cancun, Mexico.
  • R. Moghadam and S. Jagannathan, 2020, Optimal Adaptive Regulation of Uncertain Linear Continuous-time Systems with State and Input Delays, 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Korea (South), 132-137
  • R. Moghadam, P. Natarajan and S. Jagannathan, 2020, Multilayer Neural Network-based Optimal Adaptive Tracking Control of Partially Uncertain Nonlinear Discrete-time Systems, 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Korea (South), 2204-2209
  • R. Moghadam and S. Jagannathan, 2020, Optimal Control of Linear Continuous-time Systems in the Presence of State and Input Delays with Application to a Chemical Reactor, American Control Conference (ACC), Denver, CO, USA, 999-1004
  • R. Moghadam, P. Natarajan, K. Raghavan and S. Jagannathan, 2020, Online Optimal Adaptive Control of a Class of Uncertain Nonlinear Discrete-time Systems International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom,1-6
  • R. Moghadam and S. Jagannathan, 2019, Approximate Optimal Adaptive Control of Partially Unknown Linear Continuous-time Systems with State Delay, IEEE 58th Conference on Decision and Control (CDC), Nice, France, 1985-1990
  • V. Narayanan, S. Jagannathan, R. Moghadam, 2019, Optimality in Event-triggered Adaptive Control of Uncertain Linear Dynamical Systems, AIAA Scitech 2019 Forum, ed: American Institute of Aeronautics and Astronautics, San Diego, CA, USA, 1-8
  • R. Moghadam and H. Modares, 2017, An internal model principle for the attacker in distributed control systems, IEEE 56th Annual Conference on Decision and Control (CDC). 6604-6609
  • R. Moghadam, Q. Wei, and H. Modares, 2017, Distributed Control of Leader-follower Systems under Adversarial Inputs Using Reinforcement Learning, IEEE Symposium Series on Computational Intelligence (SSCI), Honolulu, HI, USA,1-8.