Ankush Chakrabarty

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 74

Top Topics

Control Policies

Reinforcement Learning

Approximate Dynamic Programming

Predictive Control

Top Venues

IEEE Trans. Control. Syst. Technol.

Publications

Sleiman Safaoui, Abraham P. Vinod, Ankush Chakrabarty, Rien Quirynen, Nobuyuki Yoshikawa, Stefano Di Cairano
Safe Multiagent Motion Planning Under Uncertainty for Drones Using Filtered Reinforcement Learning. IEEE Trans. Robotics 40 (2024)
Wei-Ting Tang, Ankush Chakrabarty, Joel A. Paulson
BEACON: A Bayesian Optimization Strategy for Novelty Search in Expensive Black-Box Systems. CoRR (2024)
Jiaqi Yan, Ankush Chakrabarty, Alisa Rupenyan, John Lygeros
MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models. CoRR (2024)
Ankush Chakrabarty, Scott A. Bortoff, Christopher R. Laughman
Simulation Failure-Robust Bayesian Optimization for Data-Driven Parameter Estimation. IEEE Trans. Syst. Man Cybern. Syst. 53 (5) (2023)
Truong X. Nghiem, Ján Drgona, Colin N. Jones, Zoltán Nagy, Roland Schwan, Biswadip Dey, Ankush Chakrabarty, Stefano Di Cairano, Joel A. Paulson, Andrea Carron, Melanie N. Zeilinger, Wenceslao Shaw-Cortez, Draguna L. Vrabie
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems. ACC (2023)
Alessandro Salatiello, Ye Wang, Gordon Wichern, Toshiaki Koike-Akino, Yoshihiro Ohta, Yosuke Kaneko, Christopher R. Laughman, Ankush Chakrabarty
Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between? e-Energy (Companion) (2023)
Claus Danielson, Scott A. Bortoff, Ankush Chakrabarty
Extremum Seeking Control With an Adaptive Gain Based on Gradient Estimation Error. IEEE Trans. Syst. Man Cybern. Syst. 53 (1) (2023)
Joel A. Paulson, Farshud Sorourifar, Christopher R. Laughman, Ankush Chakrabarty
LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems. ACC (2023)
Raphael Chinchilla, Vedang M. Deshpande, Ankush Chakrabarty, Christopher R. Laughman
Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles. ACC (2023)
Sleiman Safaoui, Abraham P. Vinod, Ankush Chakrabarty, Rien Quirynen, Nobuyuki Yoshikawa, Stefano Di Cairano
Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning. CoRR (2023)
Truong X. Nghiem, Ján Drgona, Colin N. Jones, Zoltán Nagy, Roland Schwan, Biswadip Dey, Ankush Chakrabarty, Stefano Di Cairano, Joel A. Paulson, Andrea Carron, Melanie N. Zeilinger, Wenceslao Shaw-Cortez, Draguna L. Vrabie
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems. CoRR (2023)
Vedang M. Deshpande, Ankush Chakrabarty, Abraham P. Vinod, Christopher R. Laughman
Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States. IEEE Control. Syst. Lett. 7 (2023)
Wenjie Xu, Colin N. Jones, Bratislav Svetozarevic, Christopher R. Laughman, Ankush Chakrabarty
Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints. CoRR (2023)
Joel A. Paulson, Farshud Sorourifar, Ankush Chakrabarty
Efficient Multi-Step Lookahead Bayesian Optimization with Local Search Constraints. CDC (2022)
Ankush Chakrabarty
Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach. CDC (2022)
Yehan Ma, Jianlin Guo, Yebin Wang, Ankush Chakrabarty, Heejin Ahn, Philip V. Orlik, Xinping Guan, Chenyang Lu
Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems. IEEE Trans. Control. Syst. Technol. 30 (6) (2022)
Sanjana Vijayshankar, Ankush Chakrabarty, Piyush Grover, Saleh Nabi
Co-design of reduced-order models and observers from thermo-fluid data. IFAC J. Syst. Control. 19 (2022)
Ankush Chakrabarty
Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach. CoRR (2022)
Marcel Menner, Ankush Chakrabarty, Karl Berntorp, Stefano Di Cairano
Learning Optimization-based Control Policies Directly from Digital Twin Simulations. CCTA (2022)
Ankush Chakrabarty, Gordon Wichern, Christopher R. Laughman
Meta-Learning of Neural State-Space Models Using Data From Similar Systems. CoRR (2022)
Ankush Chakrabarty, Claus Danielson, Stefano Di Cairano, Arvind U. Raghunathan
Active Learning for Estimating Reachable Sets for Systems With Unknown Dynamics. IEEE Trans. Cybern. 52 (4) (2022)
Shen Wang, Ankush Chakrabarty, Ahmad F. Taha
Data-Driven Identification of Dynamic Quality Models in Drinking Water Networks. CoRR (2022)
Abraham P. Vinod, Sleiman Safaoui, Ankush Chakrabarty, Rien Quirynen, Nobuyuki Yoshikawa, Stefano Di Cairano
Safe multi-agent motion planning via filtered reinforcement learning. ICRA (2022)
Wenjie Xu, Colin N. Jones, Bratislav Svetozarevic, Christopher R. Laughman, Ankush Chakrabarty
VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints. ACC (2022)
Shamma Nasrin, Ahish Shylendra, Nastaran Darabi, Theja Tulabandhula, Wilfred Gomes, Ankush Chakrabarty, Amit Ranjan Trivedi
ENOS: Energy-Aware Network Operator Search in Deep Neural Networks. IEEE Access 10 (2022)
Abhishek Cauligi, Ankush Chakrabarty, Stefano Di Cairano, Rien Quirynen
PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control. L4DC (2022)
Shen Wang, Ahmad F. Taha, Ankush Chakrabarty, Lina Sela, Ahmed A. Abokifa
Model Order Reduction for Water Quality Dynamics. CoRR (2021)
Ankush Chakrabarty, Gordon Wichern, Christopher R. Laughman
Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins. CoRR (2021)
Wenjie Xu, Colin N. Jones, Bratislav Svetozarevic, Christopher R. Laughman, Ankush Chakrabarty
VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints. CoRR (2021)
Ankush Chakrabarty, Rien Quirynen, Diego Romeres, Stefano Di Cairano
Learning Disagreement Regions with Deep Neural Networks to Reduce Practical Complexity of Mixed-Integer MPC. SMC (2021)
Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang, Kyriakos G. Vamvoudakis
Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation. IEEE Trans. Neural Networks Learn. Syst. 32 (1) (2021)
Karl Berntorp, Ankush Chakrabarty, Stefano Di Cairano
Vehicle Center-of-Gravity Height and Dynamics Estimation with Uncertainty Quantification by Marginalized Particle Filter. ACC (2021)
Karl Berntorp, Ankush Chakrabarty, Stefano Di Cairano
Vehicle Rollover Avoidance by Parameter-Adaptive Reference Governor. CDC (2021)
Claus Danielson, Scott A. Bortoff, Ankush Chakrabarty
Extremum Seeking Control with an Adaptive Gain Based On Gradient Estimation Error. CoRR (2021)
Gordon Wichern, Ankush Chakrabarty, Zhong-Qiu Wang, Jonathan Le Roux
Anomalous Sound Detection Using Attentive Neural Processes. WASPAA (2021)
Ankush Chakrabarty, Scott A. Bortoff, Christopher R. Laughman
Simulation Failure Robust Bayesian Optimization for Estimating Black-Box Model Parameters. SMC (2021)
Ankush Chakrabarty, Mouhacine Benosman
Safe learning-based observers for unknown nonlinear systems using Bayesian optimization. Autom. 133 (2021)
Ankush Chakrabarty, Elizabeth Healey, Dawei Shi, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
Embedded Model Predictive Control for a Wearable Artificial Pancreas. IEEE Trans. Control. Syst. Technol. 28 (6) (2020)
Sanjana Vijayshankar, Saleh Nabi, Ankush Chakrabarty, Piyush Grover, Mouhacine Benosman
Dynamic Mode Decomposition and Robust Estimation: Case Study of a 2D Turbulent Boussinesq Flow. ACC (2020)
Ankush Chakrabarty, Claus Danielson, Yebin Wang
Data-Driven Optimal Tracking with Constrained Approximate Dynamic Programming for Servomotor Systems. CCTA (2020)
Ankush Chakrabarty, Karl Berntorp, Stefano Di Cairano
Learning-based Parameter-Adaptive Reference Governors. ACC (2020)
Arnab Raha, Ankush Chakrabarty, Vijay Raghunathan, Gregery T. Buzzard
Embedding Approximate Nonlinear Model Predictive Control at Ultrahigh Speed and Extremely Low Power. IEEE Trans. Control. Syst. Technol. 28 (3) (2020)
Ankush Chakrabarty, Mouhacine Benosman
Safe Learning-based Observers for Unknown Nonlinear Systems using Bayesian Optimization. CoRR (2020)
Yebin Wang, Ankush Chakrabarty, MengChu Zhou, Jinyun Zhang
Near-Optimal Control of Motor Drives via Approximate Dynamic Programming. SMC (2019)
Ankush Chakrabarty, Devesh K. Jha, Yebin Wang
Data-Driven Control Policies for Partially Known Systems via Kernelized Lipschitz Learning. ACC (2019)
Martin Corless, Ankush Chakrabarty
L2Observers for a Class of Nonlinear Systems with Unknown Inputs. ECC (2019)
Ankush Chakrabarty, Devesh K. Jha, Gregery T. Buzzard, Yebin Wang, Kyriakos G. Vamvoudakis
Safe Approximate Dynamic Programming Via Kernelized Lipschitz Estimation. CoRR (2019)
Yehan Ma, Jianlin Guo, Yebin Wang, Ankush Chakrabarty, Heejin Ahn, Philip V. Orlik, Chenyang Lu
Optimal dynamic scheduling of wireless networked control systems. ICCPS (2019)
Ankush Chakrabarty, Rien Quirynen, Claus Danielson, Weinan Gao
Approximate Dynamic Programming For Linear Systems with State and Input Constraints. ECC (2019)
Ankush Chakrabarty, Rien Quirynen, Claus Danielson, Weinan Gao
Approximate Dynamic Programming For Linear Systems with State and Input Constraints. CoRR (2019)
Ankush Chakrabarty, Ali Zemouche, Rajesh Rajamani, Mouhacine Benosman
Robust Data-Driven Neuro-Adaptive Observers With Lipschitz Activation Functions. CDC (2019)
Olivia Choudhury, Ankush Chakrabarty, Scott J. Emrich
Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation. IEEE ACM Trans. Comput. Biol. Bioinform. 16 (4) (2019)
Uros Kalabic, Ankush Chakrabarty, Rien Quirynen, Stefano Di Cairano
Learning autonomous vehicle passengers' preferred driving styles using g-g plots and haptic feedback. ITSC (2019)
Martin J. Corless, Ankush Chakrabarty
L2 Observers for a Class of Nonlinear Systems with Unknown Inputs. CoRR (2019)
John H. Abel, Ankush Chakrabarty, Elizabeth B. Klerman, Francis J. Doyle III
Pharmaceutical-based entrainment of circadian phase via nonlinear model predictive control. Autom. 100 (2019)
Ankush Chakrabarty, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems. IEEE Trans. Biomed. Eng. 65 (3) (2018)
Ankush Chakrabarty, Emilia Fridman, Stanislaw H. Zak, Gregery T. Buzzard
State and unknown input observers for nonlinear systems with delayed measurements. Autom. 95 (2018)
Ankush Chakrabarty, Arvind U. Raghunathan, Stefano Di Cairano, Claus Danielson
Data-Driven Estimation of Backward Reachable and Invariant Sets for Unmodeled Systems via Active Learning. CDC (2018)
Ankush Chakrabarty, Ann E. Rundell, Stanislaw H. Zak, Fanglai Zhu, Gregery T. Buzzard
Unknown Input Estimation for Nonlinear Systems Using Sliding Mode Observers and Smooth Window Functions. SIAM J. Control. Optim. 56 (5) (2018)
Ankush Chakrabarty, Francis J. Doyle, Eyal Dassau
Deep Learning Assisted Macronutrient Estimation For Feedforward-Feedback Control In Artificial Pancreas Systems. ACC (2018)
Ankush Chakrabarty, Martin J. Corless, Gregery T. Buzzard, Stanislaw H. Zak, Ann E. Rundell
State and Unknown Input Observers for Nonlinear Systems With Bounded Exogenous Inputs. IEEE Trans. Autom. Control. 62 (11) (2017)
Stanislaw H. Zak, Ankush Chakrabarty, Gregery T. Buzzard
Robust state and unknown input estimation for nonlinear systems characterized by incremental multiplier matrices. ACC (2017)
Ankush Chakrabarty, Raid Ayoub, Stanislaw H. Zak, Shreyas Sundaram
Delayed unknown input observers for discrete-time linear systems with guaranteed performance. Syst. Control. Lett. 103 (2017)
Ankush Chakrabarty, Vu C. Dinh, Martin J. Corless, Ann E. Rundell, Stanislaw H. Zak, Gregery T. Buzzard
Support Vector Machine Informed Explicit Nonlinear Model Predictive Control Using Low-Discrepancy Sequences. IEEE Trans. Autom. Control. 62 (1) (2017)
Ankush Chakrabarty, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
Model predictive control with event-triggered communication for an embedded artificial pancreas. CCTA (2017)
Arnab Raha, Ankush Chakrabarty, Vijay Raghunathan, Gregery T. Buzzard
Ultrafast embedded explicit model predictive control for nonlinear systems. ACC (2017)
Ankush Chakrabarty, Stamatina Zavitsanou, Francis J. Doyle, Eyal Dassau
Reducing controller updates via event-triggered model predictive control in an embedded artificial pancreas. ACC (2017)
Ankush Chakrabarty, Gregery T. Buzzard, Stanislaw H. Zak
Output-Tracking Quantized Explicit Nonlinear Model Predictive Control Using Multiclass Support Vector Machines. IEEE Trans. Ind. Electron. 64 (5) (2017)
Ankush Chakrabarty, Stanislaw H. Zak, Shreyas Sundaram
State and unknown input observers for discrete-time nonlinear systems. CDC (2016)
Ankush Chakrabarty, Gregery T. Buzzard, Emilia Fridman, Stanislaw H. Zak
Unknown input estimation via observers for nonlinear systems with measurement delays. CDC (2016)
Xiaohang Li, Fanglai Zhu, Ankush Chakrabarty, Stanislaw H. Zak
Nonfragile Fault-Tolerant Fuzzy Observer-Based Controller Design for Nonlinear Systems. IEEE Trans. Fuzzy Syst. 24 (6) (2016)
Ankush Chakrabarty, Shreyas Sundaram, Martin J. Corless, Gregery T. Buzzard, Stanislaw H. Zak, Ann E. Rundell
Distributed unknown input observers for interconnected nonlinear systems. ACC (2016)
Olivia Choudhury, Ankush Chakrabarty, Scott J. Emrich
HAPI-Gen: Highly Accurate Phasing and Imputation of Genotype Data. BCB (2016)
Haotian Zhang, Ankush Chakrabarty, Raid Ayoub, Gregery T. Buzzard, Shreyas Sundaram
Sampling-based explicit nonlinear model predictive control for output tracking. CDC (2016)
Ankush Chakrabarty, Gregery T. Buzzard, Stanislaw H. Zak, Fanglai Zhu, Ann E. Rundell
Simultaneous Unknown Input And Sensor Noise Reconstruction For Nonlinear Systems With Boundary Layer Sliding Mode Observers. CoRR (2015)
Ankush Chakrabarty, Vu C. Dinh, Gregery T. Buzzard, Stanislaw H. Zak, Ann E. Rundell
Robust explicit nonlinear model predictive control with integral sliding mode. ACC (2014)
Ankush Chakrabarty, Gregery T. Buzzard, Martin J. Corless, Stanislaw H. Zak, Ann E. Rundell
Correcting hypothalamic-pituitary-adrenal axis dysfunction using observer-based explicit nonlinear model predictive control. EMBC (2014)
Ankush Chakrabarty, Serena M. Pearce, Robert P. Nelson, Ann E. Rundell
Treating acute myeloid leukemia via HSC transplantation: A preliminary study of multi-objective personalization strategies. ACC (2013)
Ankush Chakrabarty, Harsh Jain, Amitava Chatterjee
Volterra kernel based face recognition using artificial bee colonyoptimization. Eng. Appl. Artif. Intell. 26 (3) (2013)
Ankush Chakrabarty, Olivia Choudhury, Pallab Sarkar, Avishek Paul, Debarghya Sarkar
Hyperspectral image classification incorporating bacterial foraging-optimized spectral weighting. Artif. Intell. Res. 1 (1) (2012)
Suvadeep Banerjee, Ankush Chakrabarty, Sayan Maity, Amitava Chatterjee
Feedback linearizing indirect adaptive fuzzy control with foraging based on-line plant model estimation. Appl. Soft Comput. 11 (4) (2011)