Advances in Process Control I | AIChE

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Advances in Process Control I

Chair(s)

Paulson, J., The Ohio State University

Co-chair(s)

Babaei Pourkargar, D., Kansas State University

This session seeks to showcase novel theoretical and methodological developments in process control with applications in both traditional and emerging topics in the process control field. Current developments related to nonlinear and multiscale systems as well as applications in nontraditional settings are especially welcome.

Presentations

8:00 AM
(207a) Offline Reinforcement Learning for Control of Complex Chemical Processes
8:18 AM
(207b) Entropy-Maximizing TD3-Based Reinforcement Learning for Controlling and Optimizing Complex Dynamical Systems
8:36 AM
(207c) Necessary Optimality-Constrained Bayesian Optimization (NOBO) for Efficiently Learning Complex Control Policies from Closed-Loop Data
8:54 AM
(207d) Moving Horizon Estimation for Diffusion-Transport-Reaction Systems: A Late-Lumping Approach
9:12 AM
(207e) A Systematic Approach for Controlling Processes Outside the Training Region of Data-Driven Models
9:30 AM
(207f) Model Predictive-Based Detection of Cyberattacks on Actuators Controlling Nonlinear Systems with Changing Process Dynamics
9:48 AM
(207g) Learning-Based Data Reconstruction and Predictive Modeling of an Ammonia Synthesis Process for State Estimation and Control Applications
10:06 AM
(207h) Simulated Greenhouse Lighting Control Test Bed Utilizing Ray Tracing and Image Detection to Study Control and Modeling Considerations Using Classical and Quantum Computing

Topics 

Process Automation & Control

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Pricing

Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00

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