POLURI SRI MANNARAYANA
ACE Engineering College, Vignan's Lara Institute of Technology & Science, National Institute of Technology Durgapur
About
Dr. Srimannarayana Poluri received his B.Tech in Electrical and Electronics Engineering from Bapatla Engineering College, Bapatla, Acharya Nagarjuna University, Andhra Pradesh, India in 2014 and M.Tech in Power Systems Engineering from National Institute of Technology Agartala, Tripura, India in 2018. He is currently pursuing PhD in Electrical Engineering from National Institute of Technology Durgapur, West Bengal, India. His research interests include power system load frequency control and nonlinear estimation.
Employment
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ACE Engineering College Assistant Professor2026 - Present
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Vignan's Lara Institute of Technology & Science Assistant Professor2024 - 2026
Education
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National Institute of Technology Durgapur PhD2019 - Present
Projects & Funding
Projects & funding information is unavailable.
Publications (11)
- Adaptive Variational Bayesian Cubature Quadrature Kalman Filter With Randomly Delayed Measurements and Unknown Noise Covariance Matrices Save
- Adaptive Kalman filter based on variational Bayesian approach for one-step randomly delayed measurements Save
- Adaptive Gaussian filters for nonlinear state estimation with one-step randomly delayed measurements Save
- A Realistic Approach Towards Solution of Load Frequency Control Problem in Interconnected Power Systems Save
- Adaptive cubature quadrature Kalman filter for nonlinear state estimation with one step randomly delayed measurements Save
- Nonlinear State Estimation Using Adaptive Gaussian Filters with One-Step Randomly Delayed Measurements Save
- Transformed Cubature Quadrature Kalman Filter for Harmonic Estimation with one-step Randomly Delayed Measurements Save
- Estimation of the State-of-Charge of Lithium-ion Battery using Adaptive State Augmented Cubature Kalman Filter in Presence of Uncharacterized Coloured Noise in the Measurement Save
- Adaptive cubature quadrature Kalman filter for nonlinear state estimation with one step randomly delayed measurements Save
- State of Charge Estimation of Lithium-Ion Battery Using State Augmented Cubature Kalman Filter in Presence of Uncharacterized Coloured Noise Save