2024 AIChE Annual Meeting

Session: 10B: AI/ML Modeling, Optimization and Control Applications I

This session welcomes contributions related to the application of AI/ML technologies for Modeling, Control, Estimation and Optimization. Applications related to novel topics as well as industrial and manufacturing contributions that highlights AI/ML methods are highly encouraged.

Chair

He, Q. P., Auburn University

Co-Chairs

Jain, A., Sparkcognition
Lu, C., Ohio State University, Department of Chemical and

Presentations

12:30 PM

(674a) Enhancing Understanding of MPC Control Actions through Explainable AI Approaches

12:46 PM

(372ak) A Practical Reinforcement Learning (RL)-Based Controller Design for Distillation Columns

01:02 PM

(674c) Benchmarking Surrogate Embedding Strategies for Model Predictive Control

01:18 PM

(674d) Hybrid Gaussian Radial Basis Neural Networks (GRAB-NN): Development, Training, and Applications to Modeling Nonlinear Dynamic Noisy Chemical Processes

01:34 PM

(674e) Sample-Efficient High-Dimensional MPC Tuning Using Bayesian Optimization over Sparse Axis-Aligned Subspaces

01:50 PM

(674f) Towards Continuous Manufacturing By Enhancing Real-Time Slug-Flow Crystallization Analysis Using Noninvasive Inline Imaging and Computer Vision

02:06 PM

(674g) End-to-End Control Policy Learning through Implicit Differentiation with World Models

02:22 PM

(674h) Machine Learning Based Controller Design for a Wastewater Treatment Plant Benchmark

02:38 PM

(674i) Accelerated Modeling of Various Chemical Processes Using Meta-Learning-Based Foundation Models: A Few-Shot Learning Approach Using Reptile