383 Process Modeling and Identification


Description:
This session will highlight data driven and first-principles approaches to process modeling and identification.

Sponsor:
Systems and Process Control


Chair:
Daniel Chen
Lamar University
Dan F. Smith Department of Chemical Engineering
Beaumont, TX
77710
Email: daniel.chen@lamar.edu

Co-Chair:
Q. Peter He
Associate Professor
Auburn University
Chemical Engineering
Auburn, AL
36088
Fax Number: 334-724-4188
Email: qhe@mytu.tuskegee.edu


Papers:
383a
Virtual Metrology As a Big Data Solution to Semiconductor Manufacturing
Kerul Suthar, Auburn University; Devarshi Shah, Auburn University; Q. Peter He, Auburn University
383b
Enabling Discovery and Integration of Process Models and Data Using Ontology in the Domain of Biorefining
Linsey Koo, University of Surrey; Edlira Kalemi, University of Surrey; Franjo Cecelja, University of Surrey
383c
Multivariable Adaptive Subspace Identification of Blood Glucose Concentration Dynamics for People with Type 1 Diabetes Mellitus
Iman Hajizadeh, Illinois Institute of Technology; Mudassir Rashid, Illinois Institute of Technology; Sediqeh Samadi, Illinois Institute of Technology; Mert Sevil, Illinois Institute of Technology; Nicole Frantz, Illinois Institute of Technology; Jianyuan Feng, Illinois Institute of Technology; Caterina Lazaro, Illinois Institute of Technology; Zacharie Maloney, Illinois Institute of Technology; Rachel Brandt, Illinois Institute of Technology; Xia Yu, Northeastern University; Kamuran Turksoy, Illinois Institute of Technology; Elizabeth Littlejohn, University of Chicago; Ali Cinar, Illinois Institute of Technology
383d
Model Reduction and Approximation for Simultaneous Design, Control, and Scheduling
Justin Katz, Texas A&M University; Baris Burnak, Texas A&M University; Nikolaos A. Diangelakis, Texas A&M University; Efstratios N. Pistikopoulos, Texas A&M University
383e
Handling Delayed and Irregular Measurements in Batch Subspace Model Identification Framework
Abhinav Garg, McMaster University; Prashant Mhaskar, McMaster University
383f
Design of Experiments for Identification of Model That Is Suitable for Use in Control System
Shobhit Misra, Chemical & Biomolecular Engineering, University of Houston; Michael Nikolaou, University of Houston
383g
How Does a Control Room Operator Identify the Process?  Insights Using a Cognitive Engineering Approach
Laya Das, Indian Institute of Technology Gandhinagar; Babji Srinivasan, Indian Institute of Technology Gandhinagar; Rajagopalan Srinivasan, Indian Institute of Technology Gandhinagar
383h
Predictive Control of Lake Levels and Estimation of Stream Flows for the Adaptive      Management Complex Natural Watersheds. Part 1. Estimation
Jeffrey C. Kantor, University of Notre Dame
383i
Predictive Control of Lake Levels and Estimation of Stream Flows for the Adaptive Management Complex Natural Watersheds. Part 2. Economic Model Predictive Control
Jeffrey C. Kantor, University of Notre Dame
Abstract Submissions Closed
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