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.
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Journal ArticleDOI
Sensor network design based on system-wide reliability criteria. Part I: Objectives
TL;DR: A modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process is presented.
Proceedings ArticleDOI
Electrical circuit analysis of CO poisoning in high temperature PEM fuel cells for rapid fault diagnostics
TL;DR: In this paper, a detailed study on the impact of CO poisoning on the performance of high temperature PEM fuel cells is presented, which can be used to track the fuel cell state of health.
Journal ArticleDOI
An integrated approach for oscillation diagnosis in linear closed loop systems
TL;DR: In this paper, an integrated approach to diagnose both single/multiple root causes in single input single output (SISO) loops is presented, where simulation and industrial case studies are provided to show the applicability of the proposed algorithms.
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Multivariable gain-scheduled fuzzy logic control of a fluidized catalytic cracker unit
TL;DR: The key FLC modification is the use of a sigmoidal gain-schedule (SGS) that is the significantly parameter-reduced equivalent of a flexible fuzzy input/output variable.
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Modeling of rechargeable batteries
TL;DR: While the state of the art in modeling is described, avenues for future research work in this area are also identified and a new classification of the models as being first principles based, surrogate first principlesbased, data-based and/or a hybrid of first principles and data based approaches are proposed.