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UID:20260619T121813EDT-8177kWd6eb@132.216.98.100
DTSTAMP:20260619T161813Z
DESCRIPTION:Virtual Informal Systems Seminar (VISS) Centre for Intelligent 
 Machines (CIM) and Groupe d'Etudes et de Recherche en Analyse des Decision
 s (GERAD)\n\n\n	\n		\n			\n				\n					\n						\n							\n								\n									Zoom Link\n									Meeting ID: 910 7928 6959       
  \n									Passcode: VISS\n							\n						\n					\n				\n			\n		\n	\n\n\n \n\nSpeaker: Jun Liu\, Associate Pro
 fessor\, Applied Mathematics\, University of Waterloo\n	\n	Abstract: Formal 
 methods for control aim to synthesize controllers for continuous dynamical
  systems to meet high-level specifications. Finite abstractions\, also kno
 wn as symbolic models\, have provided useful means for algorithmically syn
 thesizing hybrid controllers with respect to rigorous specifications (e.g.
 \, safety\, reachability\, or more generally a temporal logic formula). A 
 central theoretical question surrounding abstraction-based control is whet
 her one can decide\, through finite abstractions and discrete synthesis\, 
 the existence of a controller for a nonlinear system to satisfy a given sp
 ecification. This question may also have practical implications towards ad
 dressing the inherent scalability issues of abstraction-based approaches.
 \n	\n	In this talk\, we discuss some recent results towards answering this q
 uestion. We first introduce a method to synthesize robust controllers for 
 temporal logic formulas using finite abstractions. We then use this notion
  of robustness to show that\, if a system robustly satisfies a given speci
 fication\, then it is possible to use discrete abstractions to synthesize 
 a robust controller. Following this\, we present a specification-guided fr
 amework to improve the computational performance of abstraction-based meth
 ods\, while providing the same theoretical guarantees. We conclude by argu
 ing that the intrinsic robustness and controllability of the underlying dy
 namical system can and should be exploited to address the scalability issu
 es caused by discretization of continuous dynamics and to mitigate the com
 binatorial explosion imposed by logic specifications.\n	\n	Biography: Jun Li
 u is an Associate Professor in Applied Mathematics at the University of Wa
 terloo. He received the Ph.D. degree in Applied Mathematics from the Unive
 rsity of Waterloo in 2011. From 2011 to 2012\, he held an NSERC Postdoctor
 al Fellowship in Control and Dynamical Systems at Caltech. From 2012 to 20
 15\, he was a Lecturer in Control and Systems Engineering at the Universit
 y of Sheffield. His main research interests are in the theory and applicat
 ions of hybrid systems and control\, including rigorous computational meth
 ods for control design with applications in cyber-physical systems and rob
 otics. He was awarded a Tier 2 Canada Research Chair from the Government o
 f Canada in 2017\, an Ontario Early Researcher Award in 2018\, and an Earl
 y Career Award from the Canadian Applied and Industrial Mathematics Societ
 y and Pacific Institute for the Mathematical Sciences (CAIMS/PIMS) in 2020
 .  He was a co-recipient of the Nonlinear Analysis: Hybrid Systems Paper P
 rize at the 2017 IFAC World Congress. \n
DTSTART:20210319T180000Z
DTEND:20210319T190000Z
LOCATION:CA\, ZOOM
SUMMARY:Formal Methods for Nonlinear Control: A Robustness Perspective
URL:/cim/channels/event/formal-methods-nonlinear-contr
 ol-robustness-perspective-329337
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