Ankush Chakrabarty

CoRR, January, 2025

2024

Safe Multiagent Motion Planning Under Uncertainty for Drones Using Filtered Reinforcement Learning.

[BibT_eX]

[DOI]

IEEE Trans. Robotics, 2024

Coactive Preference-Guided Multi-Objective Bayesian Optimization: An Application to Policy Learning in Personalized Plasma Medicine.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2024

BEACON: A Bayesian Optimization Strategy for Novelty Search in Expensive Black-Box Systems.

[BibT_eX]

[DOI]

Wei-Ting Tang

Joel A. Paulson

CoRR, 2024

Physics-Constrained Meta-Learning for Online Adaptation and Estimation in Positioning Applications.

[BibT_eX]

[DOI]

Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

Bayesian Forecasting with Deep Generative Disturbance Models in Stochastic MPC for Building Energy Systems.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Control Technology and Applications, 2024

Assessing Building Control Performance Using Physics-Based Simulation Models and Deep Generative Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Control Technology and Applications, 2024

MPC of Uncertain Nonlinear Systems with Meta-Learning for Fast Adaptation of Neural Predictive Models.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Automation Science and Engineering, 2024

Aircraft Approach Management Using Reachability and Dynamic Programming.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2024

2023

Simulation Failure-Robust Bayesian Optimization for Data-Driven Parameter Estimation.

[BibT_eX]

[DOI]

Scott A. Bortoff

IEEE Trans. Syst. Man Cybern. Syst., May, 2023

Extremum Seeking Control With an Adaptive Gain Based on Gradient Estimation Error.

[BibT_eX]

[DOI]

Scott A. Bortoff

IEEE Trans. Syst. Man Cybern. Syst., 2023

Physics-Constrained Deep Autoencoded Kalman Filters for Estimating Vapor Compression System States.

[BibT_eX]

[DOI]

Vedang M. Deshpande

Abraham P. Vinod

IEEE Control. Syst. Lett., 2023

Safe multi-agent motion planning under uncertainty for drones using filtered reinforcement learning.

[BibT_eX]

[DOI]

CoRR, 2023

Violation-Aware Contextual Bayesian Optimization for Controller Performance Optimization with Unmodeled Constraints.

[BibT_eX]

[DOI]

Wenjie Xu

Colin N. Jones

Bratislav Svetozarevic

CoRR, 2023

Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between?

[BibT_eX]

[DOI]

Alessandro Salatiello

Proceedings of the Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023

LSR-BO: Local Search Region Constrained Bayesian Optimization for Performance Optimization of Vapor Compression Systems.

[BibT_eX]

[DOI]

Joel A. Paulson

Farshud Sorourifar

Proceedings of the American Control Conference, 2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems.

[BibT_eX]

[DOI]

Wenceslao Shaw-Cortez

Draguna L. Vrabie

Proceedings of the American Control Conference, 2023

Learning Residual Dynamics via Physics-Augmented Neural Networks: Application to Vapor Compression Cycles.

[BibT_eX]

[DOI]

Raphael Chinchilla

Vedang M. Deshpande

Proceedings of the American Control Conference, 2023

2022

Active Learning for Estimating Reachable Sets for Systems With Unknown Dynamics.

[BibT_eX]

[DOI]

Arvind U. Raghunathan

IEEE Trans. Cybern., 2022

Optimal Dynamic Transmission Scheduling for Wireless Networked Control Systems.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2022

Co-design of reduced-order models and observers from thermo-fluid data.

[BibT_eX]

[DOI]

IFAC J. Syst. Control., 2022

Meta-Learning of Neural State-Space Models Using Data From Similar Systems.

[BibT_eX]

[DOI]

Gordon Wichern

CoRR, 2022

Data-Driven Identification of Dynamic Quality Models in Drinking Water Networks.

[BibT_eX]

[DOI]

Shen Wang

Ahmad F. Taha

CoRR, 2022

ENOS: Energy-Aware Network Operator Search in Deep Neural Networks.

[BibT_eX]

[DOI]

IEEE Access, 2022

PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control.

[BibT_eX]

[DOI]

Proceedings of the Learning for Dynamics and Control Conference, 2022

Safe multi-agent motion planning via filtered reinforcement learning.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Efficient Multi-Step Lookahead Bayesian Optimization with Local Search Constraints.

[BibT_eX]

[DOI]

Joel A. Paulson

Farshud Sorourifar

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Learning Optimization-based Control Policies Directly from Digital Twin Simulations.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Control Technology and Applications, 2022

VABO: Violation-Aware Bayesian Optimization for Closed-Loop Control Performance Optimization with Unmodeled Constraints.

[BibT_eX]

[DOI]

Wenjie Xu

Colin N. Jones

Bratislav Svetozarevic

Proceedings of the American Control Conference, 2022

2021

Safe Approximate Dynamic Programming via Kernelized Lipschitz Estimation.

[BibT_eX]

[DOI]

Kyriakos G. Vamvoudakis

IEEE Trans. Neural Networks Learn. Syst., 2021

Attentive Neural Processes and Batch Bayesian Optimization for Scalable Calibration of Physics-Informed Digital Twins.

[BibT_eX]

[DOI]

Gordon Wichern

CoRR, 2021

Model Order Reduction for Water Quality Dynamics.

[BibT_eX]

[DOI]

CoRR, 2021

Safe learning-based observers for unknown nonlinear systems using Bayesian optimization.

[BibT_eX]

[DOI]

Mouhacine Benosman

Autom., 2021

Anomalous Sound Detection Using Attentive Neural Processes.

[BibT_eX]

[DOI]

Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2021

Learning Disagreement Regions with Deep Neural Networks to Reduce Practical Complexity of Mixed-Integer MPC.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021

Simulation Failure Robust Bayesian Optimization for Estimating Black-Box Model Parameters.

[BibT_eX]

[DOI]

Scott A. Bortoff

Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021

Vehicle Rollover Avoidance by Parameter-Adaptive Reference Governor.

[BibT_eX]

[DOI]

Karl Berntorp

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Vehicle Center-of-Gravity Height and Dynamics Estimation with Uncertainty Quantification by Marginalized Particle Filter.

[BibT_eX]

[DOI]

Karl Berntorp

Proceedings of the 2021 American Control Conference, 2021

2020

Embedding Approximate Nonlinear Model Predictive Control at Ultrahigh Speed and Extremely Low Power.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2020

Embedded Model Predictive Control for a Wearable Artificial Pancreas.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2020

Data-Driven Optimal Tracking with Constrained Approximate Dynamic Programming for Servomotor Systems.

[BibT_eX]

[DOI]

Yebin Wang

Proceedings of the 2020 IEEE Conference on Control Technology and Applications, 2020

Dynamic Mode Decomposition and Robust Estimation: Case Study of a 2D Turbulent Boussinesq Flow.

[BibT_eX]

[DOI]

Proceedings of the 2020 American Control Conference, 2020

Learning-based Parameter-Adaptive Reference Governors.

[BibT_eX]

[DOI]

Karl Berntorp

Proceedings of the 2020 American Control Conference, 2020

2019

Highly Accurate and Efficient Data-Driven Methods for Genotype Imputation.

[BibT_eX]

[DOI]

Olivia Choudhury

Scott J. Emrich

IEEE ACM Trans. Comput. Biol. Bioinform., 2019

L2 Observers for a Class of Nonlinear Systems with Unknown Inputs.

[BibT_eX]

[DOI]

Martin J. Corless

CoRR, 2019

Pharmaceutical-based entrainment of circadian phase via nonlinear model predictive control.

[BibT_eX]

[DOI]

Autom., 2019

Near-Optimal Control of Motor Drives via Approximate Dynamic Programming.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Learning autonomous vehicle passengers' preferred driving styles using g-g plots and haptic feedback.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

Optimal dynamic scheduling of wireless networked control systems.

[BibT_eX]

[DOI]

Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, 2019

L2Observers for a Class of Nonlinear Systems with Unknown Inputs.

[BibT_eX]

[DOI]

Martin Corless

Proceedings of the 17th European Control Conference, 2019

Approximate Dynamic Programming For Linear Systems with State and Input Constraints.

[BibT_eX]

[DOI]

Proceedings of the 17th European Control Conference, 2019

Robust Data-Driven Neuro-Adaptive Observers With Lipschitz Activation Functions.

[BibT_eX]

[DOI]

Proceedings of the 58th IEEE Conference on Decision and Control, 2019

Data-Driven Control Policies for Partially Known Systems via Kernelized Lipschitz Learning.

[BibT_eX]

[DOI]

Devesh K. Jha

Yebin Wang

Proceedings of the 2019 American Control Conference, 2019

2018

Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems.

[BibT_eX]

[DOI]

IEEE Trans. Biomed. Eng., 2018

Unknown Input Estimation for Nonlinear Systems Using Sliding Mode Observers and Smooth Window Functions.

[BibT_eX]

[DOI]

SIAM J. Control. Optim., 2018

State and unknown input observers for nonlinear systems with delayed measurements.

[BibT_eX]

[DOI]

Autom., 2018

Data-Driven Estimation of Backward Reachable and Invariant Sets for Unmodeled Systems via Active Learning.

[BibT_eX]

[DOI]

Arvind U. Raghunathan

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Deep Learning Assisted Macronutrient Estimation For Feedforward-Feedback Control In Artificial Pancreas Systems.

[BibT_eX]

[DOI]

Francis J. Doyle

Eyal Dassau

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Output-Tracking Quantized Explicit Nonlinear Model Predictive Control Using Multiclass Support Vector Machines.

[BibT_eX]

[DOI]

Gregery T. Buzzard

Stanislaw H. Zak

IEEE Trans. Ind. Electron., 2017

Support Vector Machine Informed Explicit Nonlinear Model Predictive Control Using Low-Discrepancy Sequences.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2017

State and Unknown Input Observers for Nonlinear Systems With Bounded Exogenous Inputs.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2017

Delayed unknown input observers for discrete-time linear systems with guaranteed performance.

[BibT_eX]

[DOI]

Syst. Control. Lett., 2017

Model predictive control with event-triggered communication for an embedded artificial pancreas.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Control Technology and Applications, 2017

Robust state and unknown input estimation for nonlinear systems characterized by incremental multiplier matrices.

[BibT_eX]

[DOI]

Stanislaw H. Zak

Gregery T. Buzzard

Proceedings of the 2017 American Control Conference, 2017

Ultrafast embedded explicit model predictive control for nonlinear systems.

[BibT_eX]

[DOI]

Proceedings of the 2017 American Control Conference, 2017

Reducing controller updates via event-triggered model predictive control in an embedded artificial pancreas.

[BibT_eX]

[DOI]

Proceedings of the 2017 American Control Conference, 2017

2016

Supervised learning-based explicit nonlinear model predictive control and unknown input estimation in biomedical systems

[BibT_eX]

[DOI]

PhD thesis, 2016

Nonfragile Fault-Tolerant Fuzzy Observer-Based Controller Design for Nonlinear Systems.

[BibT_eX]

[DOI]

IEEE Trans. Fuzzy Syst., 2016

Sampling-based explicit nonlinear model predictive control for output tracking.

[BibT_eX]

[DOI]

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

State and unknown input observers for discrete-time nonlinear systems.

[BibT_eX]

[DOI]

Stanislaw H. Zak

Shreyas Sundaram

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Unknown input estimation via observers for nonlinear systems with measurement delays.

[BibT_eX]

[DOI]

Proceedings of the 55th IEEE Conference on Decision and Control, 2016

HAPI-Gen: Highly Accurate Phasing and Imputation of Genotype Data.

[BibT_eX]

[DOI]

Olivia Choudhury

Scott J. Emrich

Proceedings of the 7th ACM International Conference on Bioinformatics, 2016

Distributed unknown input observers for interconnected nonlinear systems.

[BibT_eX]

[DOI]

Proceedings of the 2016 American Control Conference, 2016

2015

Simultaneous Unknown Input And Sensor Noise Reconstruction For Nonlinear Systems With Boundary Layer Sliding Mode Observers.

[BibT_eX]

[DOI]

CoRR, 2015

2014

Correcting hypothalamic-pituitary-adrenal axis dysfunction using observer-based explicit nonlinear model predictive control.

[BibT_eX]

[DOI]

Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014

Robust explicit nonlinear model predictive control with integral sliding mode.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2014

2013

Volterra kernel based face recognition using artificial bee colonyoptimization.

[BibT_eX]

[DOI]