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Sridhar Ungarala
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Associate Professor, Chemical & Biomedical Engineering
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Associate Professor, Chemical & Biomedical Engineering,
Cleveland State University
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Department of Chemical and Biomedical Engineering
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Articles
Articles
(10)
Article
A Direct Sampling Particle Filter from Approximate Conditional Density Function ...
Computers & Chemical Engineering (2011)
Sridhar Ungarala
Constraints on the state vector must be taken into account in the state estimation problem. Recently, acceptance/rejection and projection methods ...
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Article
Computing Arrival Cost Parameters in Moving Horizon Estimation Using Sampling ...
Journal of Process Control (2009)
Sridhar Ungarala
Moving horizon estimation (MHE) is a numerical optimization based approach to state estimation, where the joint probability density function (pdf) ...
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Article
Comments on "Robust and Reliable Estimation Via Unscented Recursive Nonlinear ...
Journal of Process Control (2009)
Sridhar Ungarala
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Article
Letter to the Editor
AIChE Journal (2009)
Sridhar Ungarala
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Article
The Use of a Cell Filter for State Estimation in ...
Journal of Process Control (2009)
Sridhar Ungarala and Keyu Li
Combining variants of the Kalman filter and moving horizon estimation (MHE) with nonlinear MPC has been studied before. The MHE ...
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Article
Constrained Bayesian State Estimation Using a Cell Filter
Industrial and Engineering Chemistry Research (2008)
Sridhar Ungarala, Keyu Li and Zhongzhou Chen
Constrained state estimation in nonlinear/non-Gaussian processes has been the domain of optimization based methods such as moving horizon estimation (MHE). ...
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Article
Bayesian Estimation Via Sequential Monte Carlo Sampling-Constrained Dynamic Systems
Automatica (2007)
Lixin Lang, Wen-shiang Chen, Bhavik R. Bakshi, Prem K. Goel, et al.
Nonlinear and non-Gaussian processes with constraints are commonly encountered in dynamic estimation problems. Methods for solving such problems either ignore ...
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Article
Bayesian State Estimation of Nonlinear Systems Using Approximate Aggregate Markov ...
Industrial and Engineering Chemistry Research (2006)
Sridhar Ungarala, Zhongzhou Chen and Keyu Li
The conditional probability density function (pdf) is the most complete statistical representation of the state from which optimal inferences may ...
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Article
Time-Varying System Identification Using Modulating Functions and Spline Models With ...
Computers & Chemical Engineering (2000)
Sridhar Ungarala and Tomas B. Co
Time dependent parameters are frequently encountered in many real processes which need to be monitored for process modeling, control and ...
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Article
A Multiscale, Bayesian and Error-In-Variables Approach for Linear Dynamic Data ...
Computers & Chemical Engineering (2000)
Sridhar Ungarala and Bhavik R. Bakshi
A multiscale approach to data rectification is proposed for data containing features with different time and frequency localization. Noisy data ...
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