Vedang M. Deshpande

IEEE Trans. Autom. Control., February, 2024

ℋ2/ℋ∞ Optimal Control with Sparse Sensing and Actuation.

[BibT_eX]

[DOI]

CoRR, 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

Motion Planning for Autonomous Vehicles: When Model Predictive Control Meets Ensemble Kalman Smoothing.

[BibT_eX]

[DOI]

Proceedings of the American Control Conference, 2024

2023

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

[BibT_eX]

[DOI]

Ankush Chakrabarty

Abraham P. Vinod

IEEE Control. Syst. Lett., 2023

Spectrum Sharing-Inspired Safe Motion Planning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Communications, 2023

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

[BibT_eX]

[DOI]

Raphael Chinchilla

Ankush Chakrabarty

Proceedings of the American Control Conference, 2023

2022

Sensor Placement With Optimal Precision for Temperature Estimation of Battery Systems.

[BibT_eX]

[DOI]

Kamesh Subbarao

IEEE Control. Syst. Lett., 2022

Constrained Smoothers for State Estimation of Vapor Compression Cycles.

[BibT_eX]

[DOI]

Yingbo Ma

Chris Rackauckas

Proceedings of the American Control Conference, 2022

2021

A unified framework to generate optimized compact finite difference schemes.

[BibT_eX]

[DOI]

Diego A. Donzis

J. Comput. Phys., 2021

Robust Kalman Filtering With Probabilistic Uncertainty in System Parameters.

[BibT_eX]

[DOI]

Sunsoo Kim

IEEE Control. Syst. Lett., 2021

Sparse Sensing and Optimal Precision: An Integrated Framework for H2/H∞ Optimal Observer Design.

[BibT_eX]

[DOI]

IEEE Control. Syst. Lett., 2021

Sensor Selection and Optimal Precision in H2/H∞ Estimation Framework: Theory and Algorithms.

[BibT_eX]

[DOI]

CoRR, 2021

Sparse Sensing and Optimal Precision: Robust H∞ Optimal Observer Design with Model Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the 2021 American Control Conference, 2021

Sparse Sensing Architectures with Optimal Precision for Tracking Multi-agent Systems in Sensing-denied Environments.

[BibT_eX]

[DOI]

Proceedings of the 2021 American Control Conference, 2021

2020

Sparse Sensing and Optimal Precision: Robust H∞ Optimal Observer Design with Model Uncertainty.

[BibT_eX]

[DOI]

CoRR, 2020

Data-driven Solution of Stochastic Differential Equations Using Maximum Entropy Basis Functions.

[BibT_eX]

[DOI]

CoRR, 2020

H2 Optimized PID Control of Quad-Copter Platform with Wind Disturbance.

[BibT_eX]

[DOI]

Sunsoo Kim

CoRR, 2020

Kalman Filtering with Probabilistic Uncertainty in System Parameters.

[BibT_eX]

[DOI]

Sunsoo Kim

CoRR, 2020

Sparse Sensing for H2/H∞ Optimal Observer Design with Bounded Errors.

[BibT_eX]

[DOI]

CoRR, 2020

Surrogate Modeling of Dynamics From Sparse Data Using Maximum Entropy Basis Functions.

[BibT_eX]

[DOI]

Proceedings of the 2020 American Control Conference, 2020

2019

On Improved Statistical Accuracy of Low-Order Polynomial Chaos Approximations.

[BibT_eX]

[DOI]