BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20231025T153000
DTEND;TZID=America/New_York:20231025T163000
DTSTAMP:20260404T020726
CREATED:20230825T195555Z
LAST-MODIFIED:20230825T195555Z
UID:9496-1698247800-1698251400@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Transformer-based Hybrid Modeling and Control of Evolving\, Nonlinear Processes" (Kwon\, Texas A&M University)
DESCRIPTION:Traditionally\, the dynamic modeling of chemical processes has relied on first-principles models grounded in fundamental physics and chemistry laws. These models\, primarily formulated through differential equations with constant parameters\, enable the calculation of control actions optimizing process operations\, taking both process and actuator limitations into account. However\, the ever-evolving and nonlinear nature of chemical processes frequently calls for models with time-varying parameters. Motivated by these challenges\, we have developed hybrid models that integrate system-agnostic first-principles dynamics with system-specific data-driven\, time-varying parameters. Our hybrid modeling framework incorporates a recent innovation: attention-based time-series transformers (TSTs) coupled with positional encoding. This marks a pioneering venture into applying the transformer algorithm – a cornerstone in ChatGPT’s triumph – to nonlinear\, time-varying processes. By analyzing data across both current and preceding time steps\, the TST captures both immediate and historical changes in process states\, granting a contextual insight on process dynamics\, mirroring ChatGPT’s textual context understanding. This TST-based hybrid model identifies correlations between process parameters and state variables. Its versatility is evident as it adapts to a spectrum of models – from density function theory to computational fluid dynamics -and scales\, spanning from laboratory to extensive industrial environments. We will present applications of this hybrid modeling and control architecture\, showcasing its utility from labs to industrial processes\, made possible through partnerships with leading chemical process enterprises.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-transformer-based-hybrid-modeling-and-control-of-evolving-nonlinear-processes-kwon-texas-am-university/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
END:VCALENDAR