R
Raghunathan Rengaswamy
Researcher at Indian Institute of Technology Madras
Publications - 225
Citations - 10538
Raghunathan Rengaswamy is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Proton exchange membrane fuel cell & Fault detection and isolation. The author has an hindex of 39, co-authored 210 publications receiving 9632 citations. Previous affiliations of Raghunathan Rengaswamy include Indian Institute of Technology Bombay & Bosch.
Papers
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Journal ArticleDOI
Micro photosynthetic cell for power generation from algae: Bio-electrochemical modeling and verification
Hemanth Kumar Tanneru,Resmi Suresh,Aravind Vyas Ramanan,Shahparnia Mehdi,Muthukumaran Packirisamy,Pragasen Pillay,Sheldon S. Williamson,Philippe Juneau,Raghunathan Rengaswamy +8 more
TL;DR: In this paper, a simple first-principles mathematical model is developed to predict the performance of a micro photosynthetic power cell (μPSC), an electrochemical device which generates electricity by harnessing...
Book ChapterDOI
Optimal Sensor Placement for Contamination Detection and Identification in Water Distribution Networks
TL;DR: This study designs sensor networks which satisfy the two important properties of observability and identifiability in WDNs, and uses algorithms based on greedy heuristics to solve the set covering problem.
Journal ArticleDOI
Modeling and control of battery systems. Part I: Revisiting Butler–Volmer equations to model non-linear coupling of various capacity fade mechanisms
TL;DR: An investigation and development of strategies for battery modeling and controller implementation, which are two of the essential components of any battery management system, and a generalized approach to incorporate non-linear coupling of various capacity fade mechanisms is proposed.
Journal ArticleDOI
Development of a Closed Form Nonlinear Predictive Control Law Based on a Class of Wiener Models
TL;DR: In this paper, a Wiener type model has been used for capturing dynamics of multivariable nonlinear systems with fading memory, and a closed form solution to this problem is constructed analytically using the theory of solutions of quadratic operator polynomials.
Journal ArticleDOI
A Computational Framework for Studying Gut-Brain Axis in Autism Spectrum Disorder
TL;DR: In this article , the authors present a computational framework integrating constraint based tissue specific metabolic (CBM) model and whole-body physiological pharmacokinetics (PBPK) modeling for ASD.