2017 Annual Meeting

Session: Process Modeling and Identification

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

Chair

Daniel Chen, Lamar University

Co-Chair

Q. Peter He, Auburn University

Presentations

12:30 PM

(383a) Virtual Metrology As a Big Data Solution to Semiconductor Manufacturing
Kerul Suthar, Devarshi Shah, Q. Peter He

12:47 PM

(383b) Enabling Discovery and Integration of Process Models and Data Using Ontology in the Domain of Biorefining
Linsey Koo, Edlira Kalemi, Franjo Cecelja

01:04 PM

(383c) Multivariable Adaptive Subspace Identification of Blood Glucose Concentration Dynamics for People with Type 1 Diabetes Mellitus
Iman Hajizadeh, Mudassir Rashid, Sediqeh Samadi, Mert Sevil, Nicole Frantz, Jianyuan Feng, Caterina Lazaro, Zacharie Maloney, Rachel Brandt, Xia Yu, Kamuran Turksoy, Elizabeth Littlejohn, Ali Cinar

01:21 PM

(383d) Model Reduction and Approximation for Simultaneous Design, Control, and Scheduling
Justin Katz, Baris Burnak, Nikolaos A. Diangelakis, Efstratios Pistikopoulos

01:38 PM

(383e) Handling Delayed and Irregular Measurements in Batch Subspace Model Identification Framework
Prashant Mhaskar, Abhinav Garg

01:55 PM

(383f) Design of Experiments for Identification of Model That Is Suitable for Use in Control System
Shobhit Misra, Michael Nikolaou

02:12 PM

(383g) How Does a Control Room Operator Identify the Process?  Insights Using a Cognitive Engineering Approach
Laya Das, Babji Srinivasan, Rajagopalan Srinivasan

02:29 PM

(383h) Predictive Control of Lake Levels and Estimation of Stream Flows for the Adaptive      Management Complex Natural Watersheds. Part 1. Estimation
Jeffrey C. Kantor

02:46 PM

(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