| Reduced-dimensional reinforcement learning control using singular perturbation approximations S Mukherjee, H Bai, A Chakrabortty Automatica 126, 109451, 2021 | 42 | 2021 |
| On model-free reinforcement learning of reduced-order optimal control for singularly perturbed systems S Mukherjee, H Bai, A Chakrabortty 2018 IEEE Conference on Decision and Control (CDC), 5288-5293, 2018 | 40 | 2018 |
| Scalable designs for reinforcement learning-based wide-area damping control S Mukherjee, A Chakrabortty, H Bai, A Darvishi, B Fardanesh IEEE Transactions on Smart Grid 12 (3), 2389-2401, 2021 | 29 | 2021 |
| Safe reinforcement learning for emergency load shedding of power systems TL Vu, S Mukherjee, T Yin, R Huang, J Tan, Q Huang 2021 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2021 | 18 | 2021 |
| Barrier function-based safe reinforcement learning for emergency control of power systems TL Vu, S Mukherjee, R Huang, Q Huang 2021 60th IEEE Conference on Decision and Control (CDC), 3652-3657, 2021 | 15 | 2021 |
| Learning Stochastic Parametric Diferentiable Predictive Control Policies J Drgoňa, S Mukherjee, A Tuor, M Halappanavar, D Vrabie IFAC-PapersOnLine 55 (25), 121-126, 2022 | 13 | 2022 |
| Neural lyapunov differentiable predictive control S Mukherjee, J Drgoňa, A Tuor, M Halappanavar, D Vrabie 2022 IEEE 61st Conference on Decision and Control (CDC), 2097-2104, 2022 | 11 | 2022 |
| Block-decentralized model-free reinforcement learning control of two time-scale networks S Mukherjee, A Chakrabortty, H Bai 2019 American Control Conference (ACC), 2233-2238, 2019 | 11 | 2019 |
| Reinforcement learning of structured stabilizing control for linear systems with unknown state matrix S Mukherjee, TL Vu IEEE Transactions on Automatic Control 68 (3), 1746-1752, 2022 | 10 | 2022 |
| Modeling and quantifying the impact of wind penetration on slow coherency of power systems S Mukherjee, A Chakrabortty, S Babaei IEEE Transactions on Power Systems 36 (2), 1002-1012, 2020 | 10 | 2020 |
| Scalable voltage control using structure-driven hierarchical deep reinforcement learning S Mukherjee, R Huang, Q Huang, TL Vu, T Yin arXiv preprint arXiv:2102.00077, 2021 | 9 | 2021 |
| Measurement-driven optimal control of utility-scale power systems: A New York State grid perspective S Mukherjee, S Babaei, A Chakrabortty, B Fardanesh International Journal of Electrical Power & Energy Systems 115, 105470, 2020 | 9 | 2020 |
| A measurement-based approach for optimal damping control of the New York state power grid S Mukherjee, S Babaei, A Chakrabortty 2018 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2018 | 8 | 2018 |
| On robust model-free reduced-dimensional reinforcement learning control for singularly perturbed systems S Mukherjee, H Bai, A Chakrabortty 2020 American Control Conference (ACC), 3914-3919, 2020 | 7 | 2020 |
| Economic generation scheduling in microgrid with pumped-hydro unit using particle swarm optimization S Mukherjee, R Chakraborty, SK Goswami 2015 IEEE International Conference on Electrical, Computer and Communication …, 2015 | 7 | 2015 |
| Model-based and model-free designs for an extended continuous-time LQR with exogenous inputs S Mukherjee, H Bai, A Chakrabortty Systems & Control Letters 154, 104983, 2021 | 6 | 2021 |
| Adversar: Adversarial search and rescue via multi-agent reinforcement learning A Rahman, A Bhattacharya, T Ramachandran, S Mukherjee, H Sharma, ... 2022 IEEE International Symposium on Technologies for Homeland Security (HST …, 2022 | 5 | 2022 |
| Model-free decentralized reinforcement learning control of distributed energy resources S Mukherjee, H Bai, A Chakrabortty 2020 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2020 | 5 | 2020 |
| Learning power system dynamic signatures using LSTM-based deep neural network: A prototype study on the New York state grid S Mukherjee, A Darvishi, A Chakrabortty, B Fardanesh 2019 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2019 | 5 | 2019 |
| On the stochastic stability of deep markov models J Drgona, S Mukherjee, J Zhang, F Liu, M Halappanavar Advances in Neural Information Processing Systems 34, 24033-24047, 2021 | 4 | 2021 |
Aranya ChakraborttyProfessor of Electrical EngineeringVerified email at ncsu.edu
