Search Results for author: Harish Doddi

Found 6 papers, 0 papers with code

Nonlinear Moving Horizon Estimation and Model Predictive Control for Buildings with Unknown HVAC Dynamics

no code implementations18 Nov 2022 Saman Mostafavi, Harish Doddi, Krishna Kalyanam, David Schwartz

We present a solution for modeling and online identification for heating, ventilation, and air conditioning (HVAC) control in buildings.

Management Model Predictive Control

Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs

no code implementations2 Oct 2021 Harish Doddi, Deepjyoti Deka, Saurav Talukdar, Murti Salapaka

We present a regularized non-casual consistent estimator for this problem and analyze its sample complexity over two regimes: (a) where the interval $T$ consists of $n$ i. i. d.

Estimating Linear Dynamical Networks of Cyclostationary Processes

no code implementations26 Sep 2020 Harish Doddi, Deepjyoti Deka, Saurav Talukdar, Murti Salapaka

The majority of prior work in consistent topology estimation relies on dynamical systems excited by temporally uncorrelated processes.

Tractable learning in under-excited power grids

no code implementations4 May 2020 Deepjyoti Deka, Harish Doddi, Sidhant Misra, Murti Salapaka

This paper discusses statistical structure estimation in power grids in the "under-excited" regime, where a subset of internal nodes do not have external injection.

Topology Learning of Linear Dynamical Systems with Latent Nodes using Matrix Decomposition

no code implementations16 Dec 2019 Mishfad S. V., Harish Doddi, Murti V. Salapaka

It is shown that for a large class of systems, the unique decomposition of imaginary part of the IPSDM of observed nodes, a skew symmetric matrix, into the sparse and the low-rank components is sufficient to identify the moral graph of the observed nodes as well as the Markov Blanket of latent nodes.

Retrieval

Physics Informed Topology Learning in Networks of Linear Dynamical Systems

no code implementations27 Sep 2018 Saurav Talukdar, Deepjyoti Deka, Harish Doddi, Donatello Materassi, Misha Chertkov, Murti V. Salapaka

Learning influence pathways of a network of dynamically related processes from observations is of considerable importance in many disciplines.

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