2023 AIChE Annual Meeting

Session: Interactive Session: Systems and Process Control

Presentations

03:30 PM

(149l) Harnessing Feedback Control Strategy for Improved Core Annular Flow Stability in Heavy Oil Transportation
Idelfonso Nogueira, Patrick Lima, Leizer Schnitman, Teófilo Paiva Guimarães Mendes, Erbet Costa, Sigurd Skogestad
(149ae) Bayesian Identification of Nonlinear, Sparse, Dynamic Models
Samuel Adeyemo, Debangsu Bhattacharyya
(149ac) Optimization-Based State and Parameter Estimation for Distributed Parameter Pipeline Systems
Junyao Xie, Stevan Dubljevic, Lu Zhang
(149w) Parameter Estimation in Bioprocesses Using Bayesian Inference
Nigel Mathias, Prashant Mhaskar, Brandon Corbett, Lauren Weir
(149f) Dynamic Analysis and Model Predictive Control of a Biochemical Reactor Under Delayed Uncertain Measurement and Multi-Rate Actuation/Sampling
Guilherme Ozorio Cassol, Stevan Dubljevic
(149g) Multiscale Kinetic Modeling and Optimization: In-Depth Analysis of Cellulose Degradation for Enhanced Pulping Process and Superior Paper Quality
Juhyeon Kim, Silabrata Pahari, Anqi Ji, Mairui Zhang, Chang Geun Yoo, Joseph Kwon
(149x) Hybrid Series/Parallel All-Nonlinear Dynamic-Static Stochastic Neural Networks: Development, Training and Application to Chemical Processes
Angan Mukherjee, Debangsu Bhattacharyya
(149j) Practical Control Laws with Quantum Computation
Jihan Abou Halloun, Keshav Kasturi Rangan, Helen Durand
(149ab) Considerations of Closed-Loop Control on Quantum Computers Using a Modified Grover’s Algorithm for Simulation of a Chemical Process
Kip Nieman, Helen Durand
(149y) Physics-Informed Neural Networks (PINNs) for Process Systems with Model Plant Mismatch
Prashant Mhaskar, Sarah Rasmussen, Farshad Moayedi, Samardeepsingh Sarna, Brandon Corbett
(149d) Model Predictive Control of an Axial Dispersion Tubular Reactor with Recycle: A Distributed Parameter System with State Delay
Behrad Moadeli, Stevan Dubljevic, Guilherme Ozorio Cassol
(149ad) A Constraint-Based Modeling Framework with Deep Reinforcement Learning and Multi-Objective Optimization for Control of Mammalian Cell Cultures
Essa Almutar, Satish Parulekar
(149k) Considerations of Space Manufacturing: Utilizing Earth-Based Resources for Modeling and Control Applications While Considering Communication Delay
Kip Nieman, Helen Durand
(149a) Case Studies on the Combined Identification and Offset-Free Control of Chemical Processes (Poster corresponding to plenary presentation)
Steven Kuntz, James J. Downs, Stephen M. Miller, James Rawlings
(149h) The Theoretical Basis of Ratio Control
Sigurd Skogestad
(149i) Self-Optimizing Control for Secondary Controlled Variable Selection
Chenchen Zhou, Hongxi Su, Xincheng Zhu, Fanda Pan, Yi Cao, Shuanghua Yang, Kai Shen, Mingming Hu, Kaixuan Jiao, Xinhui Tang
(149b) Fast Zone-Model Predictive Control for Full Battery Pack of Electric Vehicles
Yeonsoo Kim, Changbeom Hong, Se-Kyu Oh, Daeki Hong, Hyeonwoo Cho, Sanghoon Shin
(149c) A Machine Learning Assisted Approach to Model Predictive Control with Multi-Objective Optimization and Multi-Criteria Decision Making
Zhiyuan Wang, Wallace Tan Gian Yion, Gade Pandu Rangaiah, Zhe Wu
(149u) Advanced Model Predictive Control Strategies for Large-Scale Dynamic Systems Based on Data-Driven Artificial Neural Networks
Weiguo Xie
(149aa) Synthesis of Decarbonized Hydrogen Production Processes Using the Attainable Region Framework
Cornelius Masuku
(149e) Distributed Control of Integrated Process Systems – an Experimental Study
Priti Sukhadeve, Sujit Jogwar
(149n) Machine Learning-Based Predictive Irrigation Scheduling
Bernard Agyeman, Jinfeng Liu
(149o) Data Driven Economic Model Predictive Control of a Rotational Molding Process
Aswin Chandrasekar, Abhinav Garg, Hassan Abdulhussain, Vladimir Gritsichine, Michael R. Thompson, Prashant Mhaskar
(149p) Hybrid Subspace-Rnn Based Approach for Modelling of Non-Linear Processes
Aswin Chandrasekar, Prashant Mhaskar
(149s) Parameter Estimation for Bioprocesses Cognizant of Measurement Noise Distribution
Lauren Weir, Nigel Mathias, Prashant Mhaskar, Brandon Corbett
(149z) Reinforcement Learning Based Control of Fed-Batch Production Reactor
Mariana Monteiro, Cleo Kontoravdi, Sarah Fadda
(149q) Model-Based Control for Liquid-Liquid Extraction
Daniel Moser, Joscha Boehm, Peter Neugebauer, Stephan Sacher, Martin Horn, Jakob Rehrl, Martin Steinberger
(149v) Physics-Informed Neural Networks (PINNs) for Modeling Dynamic Processes Based on Limited Physical Knowledge and Data
Mehmet Velioglu, Manuel Dahmen, Alexander Mitsos