| State and unknown input observers for nonlinear systems with bounded exogenous inputs A Chakrabarty, MJ Corless, GT Buzzard, SH Żak, AE Rundell IEEE Transactions on Automatic Control 62 (11), 5497-5510, 2017 | 108 | 2017 |
| Event-triggered model predictive control for embedded artificial pancreas systems A Chakrabarty, S Zavitsanou, FJ Doyle, E Dassau IEEE Transactions on Biomedical Engineering 65 (3), 575-586, 2017 | 101 | 2017 |
| Non-Fragile Fault-Tolerant Fuzzy Observer-Based Controller Design for Nonlinear Systems X Li, F Zhu, A Chakrabarty, SH Zak IEEE Transactions on Fuzzy Systems 24 (6), 1679 - 1689, 2016 | 94 | 2016 |
| Intraperitoneal insulin delivery provides superior glycaemic regulation to subcutaneous insulin delivery in model predictive control‐based fully‐automated artificial pancreas … E Dassau, E Renard, J Place, A Farret, MJ Pelletier, J Lee, LM Huyett, ... Diabetes, Obesity and Metabolism 19 (12), 1698-1705, 2017 | 92 | 2017 |
| Support Vector Machine Informed Explicit Nonlinear Model Predictive Control Using Low-Discrepancy Sequences A Chakrabarty, V Dinh, M Corless, AE Rundell, SH Zak, GT Buzzard IEEE Transactions on Automatic Control 62 (1), 135 - 148, 2017 | 87 | 2017 |
| Urban sound classification using convolutional neural network and long short term memory based on multiple features JK Das, A Ghosh, AK Pal, S Dutta, A Chakrabarty 2020 Fourth International Conference On Intelligent Computing in Data …, 2020 | 60 | 2020 |
| Scalable Bayesian optimization for model calibration: Case study on coupled building and HVAC dynamics A Chakrabarty, E Maddalena, H Qiao, C Laughman Energy and Buildings 253, 111460, 2021 | 53 | 2021 |
| Volterra kernel based face recognition using artificial bee colonyoptimization A Chakrabarty, H Jain, A Chatterjee Engineering Applications of Artificial Intelligence 26 (3), 1107-1114, 2013 | 51 | 2013 |
| Model‐based design of experiments for cellular processes A Chakrabarty, GT Buzzard, AE Rundell Wiley Interdisciplinary Reviews: Systems Biology and Medicine 5 (2), 181-203, 2013 | 48 | 2013 |
| Physics-informed machine learning for modeling and control of dynamical systems TX Nghiem, J Drgoňa, C Jones, Z Nagy, R Schwan, B Dey, A Chakrabarty, ... 2023 American Control Conference (ACC), 3735-3750, 2023 | 43 | 2023 |
| Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas S Zavitsanou, A Chakrabarty, E Dassau, FJ Doyle III Processes 4 (4), 35, 2016 | 43 | 2016 |
| Active learning for estimating reachable sets for systems with unknown dynamics A Chakrabarty, C Danielson, S Di Cairano, A Raghunathan IEEE Transactions on Cybernetics 52 (4), 2531-2542, 2020 | 41 | 2020 |
| Calibrating building simulation models using multi-source datasets and meta-learned Bayesian optimization S Zhan, G Wichern, C Laughman, A Chong, A Chakrabarty Energy and Buildings 270, 112278, 2022 | 39 | 2022 |
| Accelerating self-optimization control of refrigerant cycles with Bayesian optimization and adaptive moment estimation A Chakrabarty, C Danielson, SA Bortoff, CR Laughman Applied Thermal Engineering 197, 117335, 2021 | 37 | 2021 |
| Delayed unknown input observers for discrete-time linear systems with guaranteed performance A Chakrabarty, R Ayoub, SH Żak, S Sundaram Systems & Control Letters 103, 9-15, 2017 | 36 | 2017 |
| State and unknown input observers for discrete-time nonlinear systems A Chakrabarty, SH Żak, S Sundaram 2016 IEEE 55th Conference on Decision and Control (CDC), 7111-7116, 2016 | 35 | 2016 |
| State and unknown input observers for nonlinear systems with delayed measurements A Chakrabarty, E Fridman, SH Żak, GT Buzzard Automatica 95, 246-253, 2018 | 34 | 2018 |
| Safe approximate dynamic programming via kernelized lipschitz estimation A Chakrabarty, DK Jha, GT Buzzard, Y Wang, KG Vamvoudakis IEEE transactions on neural networks and learning systems 32 (1), 405-419, 2020 | 33 | 2020 |
| Optimal dynamic scheduling of wireless networked control systems Y Ma, J Guo, Y Wang, A Chakrabarty, H Ahn, P Orlik, C Lu Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical …, 2019 | 32 | 2019 |
| VABO: Violation-aware Bayesian optimization for closed-loop control performance optimization with unmodeled constraints W Xu, CN Jones, B Svetozarevic, CR Laughman, A Chakrabarty 2022 American Control Conference (ACC), 5288-5293, 2022 | 28 | 2022 |
Christopher LaughmanSenior Principal Research Staff, Mitsubishi Electric Research LaboratoriesE-mailová adresa ověřena na: merl.com
