2021 Annual Meeting

Session: Data-Driven Techniques for Dynamic Modeling, Estimation and Control II

Chair

Qi Zhang, University of Minnesota

Co-Chair

Joseph Kwon, Texas A&M University

Presentations

12:30 PM

(303a) Data-Driven Development of Approximate Inertial Forms and Closures for Coarse-Scale Modeling of Multiphase Flows
Cristina Martin Linares, Thomas Bertalan, Ioannis G. Kevrekidis, Seungjoon Lee, Gretar Tryggvason, Jiacai Lu

12:49 PM

(303b) Combining Particle-Based Simulations and Machine Learning Models for the Prediction of Defect Kinetics in Thin Films of Symmetric Diblock Copolymers
Ludwig Schneider, Juan J. de Pablo

01:08 PM

(303c) Machine Learning-Based Predictive Control of Nonlinear Parabolic PDE Systems
Aarsh Dodhia, Zhe Wu, Panagiotis Christofides

01:27 PM

(303d) Symmetry Reduction for Deep Reinforcement Learning Active Flow Control of Chaotic Spatiotemporal Dynamics
Michael Graham, Kevin Zeng

01:46 PM

(303e) Ensuring Convexity in Constrained Optimal Control Using Input Convex Neural Networks
B. Wayne Bequette, Shu Yang

02:05 PM

(303f) Initializing the Internal States of Lstm Neural Networks Via Manifold Learning
Felix Kemeth, Thomas Bertalan, Nikolaos Evangelou, Tianqi Cui, Saurabh Malani, Ioannis G. Kevrekidis

02:24 PM

(303g) Performance-Oriented Learning of Hybrid Models for Model Predictive Control
Georgios Makrygiorgos, Angelo D. Bonzanini, Victor Miller, Ali Mesbah

02:43 PM

(303h) Learning-Based Economic Model Predictive Control for Energy Storage Systems Under Imperfect Forecast Information
David Pérez-Piñeiro, Sigurd Skogestad