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DTSTART;TZID=America/New_York:20251107T140000
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DESCRIPTION:The world is nonlinear and linked. Small-gain theory is one of 
 the most important tools to tackle fundamentally challenging control probl
 ems for interconnected linear and nonlinear systems. In this talk\, I will
  first review early developments in nonlinear small-gain theorems and asso
 ciated nonlinear control design and show how it served as a basic tool to 
 unify numerous results in constructive nonlinear control. Then\, I will pr
 esent recent developments in network/cyclic small-gain theorems for comple
 x large-scale nonlinear systems\, with a special focus on event-triggered 
 control and feedback optimization. Finally\, I will discuss briefly how ma
 chine learning techniques can be invoked to relax the conservativeness of 
 small-gain designs\, that falls into the emerging area of learning-based c
 ontrol\, a new direction in control theory.\n\nSpeaker(s): Zhong-Ping Jian
 g\, \n\nRoom: SF B560\, Bldg: SF B560\,  172 St. George St.\,\, Toronto\, 
 Ontario\, Canada\, M5R 0A3
LOCATION:Room: SF B560\, Bldg: SF B560\,  172 St. George St.\,\, Toronto\, 
 Ontario\, Canada\, M5R 0A3
ORGANIZER:mehrdad.tirandazian@ieee.org
SEQUENCE:19
SUMMARY:The Nonlinear Small-Gain Theory for Networks and Control 
URL;VALUE=URI:https://events.vtools.ieee.org/m/510444
X-ALT-DESC:Description: <br /><div>The world is nonlinear and linked. Small
 -gain theory is one of the most important tools to tackle fundamentally ch
 allenging control problems for interconnected linear and nonlinear systems
 . In this talk\, I will first review early developments in nonlinear small
 -gain theorems and associated nonlinear control design and show how it ser
 ved as a basic tool to unify numerous results in constructive nonlinear co
 ntrol. Then\, I will present recent developments in network/cyclic small-g
 ain theorems for complex large-scale nonlinear systems\, with a special fo
 cus on event-triggered control and feedback optimization. Finally\, I will
  discuss briefly how machine learning techniques can be invoked to relax t
 he conservativeness of small-gain designs\, that falls into the emerging a
 rea of learning-based control\, a new direction in control theory.</div>\n
 <div>&nbsp\;</div>
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