activity
20202026
collaborators

7 papers

math.OC2026

Identification of Nonlinear Acyclic Networks in Continuous Time from Nonzero Initial Conditions and Full Excitations

Ramachandran Anantharaman, Renato Vizuete, Julien M. Hendrickx +1

This paper addresses the identifiability and identification of nonlinear acyclic networks in continuous time when the dynamics are located on the edges and all the nodes are excite…

eess.SY2025

Data-Driven Modeling of Photosynthesis Regulation Under Oscillating Light Condition - Part I: In-Silico Exploration

Christian Portilla, Arviandy G Aribowo, Ramachandran Anantharaman +2

This paper explores the application of data-driven system identification techniques in the frequency domain to obtain simplified, control-oriented models of photosynthesis regulati…

eess.SY2025

Hierarchical Decentralized Stochastic Control for Cyber-Physical Systems

Kesav Kaza, Ramachandran Anantharaman, Rahul Meshram

This paper introduces a two-timescale hierarchical decentralized control architecture for Cyber-Physical Systems (CPS). The system consists of a global controller (GC), and N local…

eess.SY2025

Estimation of Heat Transfer Coefficient in Heat Exchangers from closed-loop data using Neural Networks

Ramachandran Anantharaman, Carlos Gonzalez Rojas, Luna Artemis van Leeuwen +1

Heat exchangers (HEXs) play a central role in process industries for thermal energy transfer. Fouling, the gradual accumulation of solids on heat transfer surfaces, causes a time-v…

eess.SY2024

Koopman operator based identification of nonlinear networks

Ramachandran Anantharaman, Alexandre Mauroy

In this work, we develop a method to identify continuous-time nonlinear networked dynamics via the Koopman operator framework. The proposed technique consists of two steps: the fir…

eess.SY2024

Dynamic Mode Decomposition with Non-uniform Sampling

Ramachandran Anantharaman, Alexandre Mauroy

Dynamic Mode Decomposition (DMD) and its extensions (EDMD) have been at the forefront of data-based approaches to Koopman operators. Most (E)DMD algorithms assume that the entire s…

cs.SC2020

On Linear Representation, Complexity and Inversion of maps over finite fields

Ramachandran Anantharaman, Virendra Sule

This paper defines a linear representation for nonlinear maps where is a finite field, in terms of matrices over .…