Process Modeling and Identification I | AIChE

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Process Modeling and Identification I

Chair(s)

Rollins, D., Iowa State University

Co-chair(s)

Misra, M., HOVENSA, LLC

This session focuses on theoretical and application results in the area of process modeling and identification. Topics of interest include, but are not limited to: data-driven and theoretical modeling, novel identification algorithms, identification and validation under conditions of inadequate and/or incomplete data, and identification ofnonlinear systems. Applications in nontraditional processes and systems are of particular interest.

Presentations

8:30 AM
(642a) An Input/Output Approach to Control of Distributed Chemical Reactors
8:50 AM
(642b) Estimation of Noise Covariances and Disturbance Structure from Data Using Least Squares with Optimal Weighting
9:10 AM
(642c) Gray-Box Modeling of an Integrated Plant with Incomplete Dynamic Information
9:30 AM
(642d) Practical Challenges in Bayesian Modeling and Elicitation of Probabilistic Information
9:50 AM
(642e) An Optimization-Based Approach to Improving the Identifiability of Nonlinear Large-Scale Systems
10:10 AM
(642f) A Continuous-Discrete Extended Kalman Filter Algorithm for Prediction-Error-Modelling
10:30 AM
(642g) Accurate Model Identification for Non-Invertible Mimo Sandwich Block-Oriented Processes

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Individuals

AIChE Pro Members $150.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00

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