340 Interactive Session: Systems and Process Control

Friday, November 20, 2020: 8:00 AM - 9:00 AM
Computing and Systems Technology Division (10) (Poster Gallery)

Description:
This poster session welcomes contributions pertaining to the development of new process analysis and control methods and/or the application of control and analysis methods to novel processes.

Sponsor:
Systems and Process Control
Co-Sponsor(s):
Poster Sessions (POSTERSESSIONS)
Chair:
Antonios Armaou Email: armaou@psu.edu
Co-Chair:
Cara Touretzky Email: cara.r.touretzky@exxonmobil.com


(340a) Comparison of Advanced Set-Based Fault Detection Methods with Classical Data-Driven and Observer-Based Methods for Nonlinear and Uncertain Chemical Processes
Bowen Mu, Xuejiao Yang and Joe Scott


(340b) Dynamic Operability Analysis of a Natural Gas Combined Cycle Power Plant Using a Novel Branch and Bound Method
San Dinh and Fernando V. Lima


(340c) Control Strategies for a Vapour Compression Refrigeration System Used in Mango Exports: An Alternative to Traditional on-Off Controllers
Manuel Merino, Laura Carrasco, Bogdan Dorneanu, Jose Manrique, Robert Menzhausen, Harvey Arellano-Garcia and William Ipanaque


(340d) Data-Driven Nonlinear System Identification of Covid-19 Pandemic Behaviour
Sarmilan Santhakumaran and Yuri Shardt


(340e) Learning Coarse-Grained Partial Differential Equations from Fine-Scale Data Via Machine Learning
Seungjoon Lee, Yorgos M. Psarellis, Hassan Arbabi, Constantinos Siettos, Felix Dietrich, Giovanni Samaey and Ioannis G. Kevrekidis


(340f) Assessing the Response of Dynamic Catalytic Surfaces
Yorgos M. Psarellis, M. Alexander Ardagh, Paul Dauenhauer and Ioannis G. Kevrekidis


(340g) White-Box Machine Learning Approaches to Identify Governing Equations for Dynamics in Complex Manufacturing Systems and Their Comparison: A Study on Distillation Column
Raghav Moar, Renganathan Subramanian and Shweta Singh


(340h) Multi-Rate Data-Driven Models for Lactic Acid Fermentation - Parameter Identification and Prediction
Jingwei Gan and Satish J. Parulekar


(340i) Multi-Objective and Hierarchical Explicit Model Predictive Control
Iosif Pappas, Styliani Avraamidou, Justin Katz, Nikolaos A. Diangelakis and Efstratios N. Pistikopoulos


(340j) Dynamic Modeling of the Industrial Methanol-to-Olefins (MTO) Process
Liang Wang and Zhihong Yuan


(340k) Subspace Model Identification and Model Predictive Control of an Industrial Ethylene Splitter
Mahir Jalanko, Prashant Mhaskar and Vladimir Mahalec


(340l) Simultaneous Design, Control and Selection of Finite Elements: A Hamiltonian Function-Profile-Based Approach.
Oscar Palma-Flores and Luis A. Ricardez Sandoval


(340m) A Method of Community Detection in Complex Weighted Networks
Leila Samandari Masooleh, Jeffrey E. Arbogast, Ulku Oktem, Warren D. Seider and Masoud Soroush


(340n) Simultaneous Economic Optimization of Organic Rankine Cycle with Working Fluids Selection and Heat Integration
Xuan Dong, Zuwei Liao, Jingyuan Sun, Binbo Jiang, Jingdai Wang and Yongrong Yang


(340o) Multi-Objective Design Optimisation of a Distributed Energy System through 3E (economic, environmental and exergy) Analysis
Sayeef Miah, Bogdan Dorneanu, Evgenia Mechleri and Harvey Arellano-Garcia


(340p) Safe Operation of Floating LNG Tank Via Model Predictive Control
Yeonpyeong Jo, Mohammed Saad Faizan Bangi, Silabrata Pahari, Joseph Sang-Il Kwon and Sungwon Hwang


(340q) Subspace-Based Model Identification for Wastewater Treatment
Emma Hermonat, Prashant Mhaskar, Rajeev Goel and Spencer Snowling


(340r) Advanced Control Strategies for Improved Subcritical Power Plant Cycling
Daniel Kestering, Selorme Agbleze, David Tucker, Lawrence J. Shadle and Fernando V. Lima


(340s) Moving Horizon Demand Response Scheduling Subject to Exogenous Uncertainties
Morgan Kelley, Ross Baldick and Michael Baldea


(340t) Process Data Analytics and Representation Learning to Predict Arc Loss in an Electric Furnace
Ibrahim Yousef, Lee Rippon, Jean-Francois Beaulieu, Carole Prévost, Bhushan Gopaluni and Sirish L. Shah
See more of this Group/Topical: Computing and Systems Technology Division
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