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Supervisory Control of Discrete Event-Driven Systems Modeled by Petri Nets

Event Type
Industrial and Enterprise Systems Engineering, Dept. Head office
Room 2240 Digital Computer Lab (1304 W. Springfield Ave, Urbana)
Jul 2, 2024   10:00 - 11:00 am  
Roshanak Khaleghi
BuuLinh Quach
Originating Calendar
ISE Seminar Calendar

*Presentation will be recorded.


The dynamics of Discrete-Event/Discrete-State (DEDS) Systems are due to an event-driven mechanism where occurrence of events at discrete points in time results in a change in the state of the system. The behavior of DEDS systems can be controlled by means of a supervisory policy, which prevents the occurrence of events at a given state of the supervised system, when deemed appropriate. In this presentation, we discuss the so-called liveness property of DEDS systems modeled by Petri Net (PN) structures. A DEDS system is live if, irrespective of the past, all its events can be executed in the future. A DEDS system is said to be deadlocked if all events of the system can never be completed. To achieve Liveness property for certain classes of PN structures, we present a learning-based algorithm that uses deadlock instances of the DEDS system, as often as necessary, to compute a Liveness Enforcing Supervisory Policy (LESP). The main motivation behind our exploration of the proposed learning algorithm is to circumvent the dependency of LESP synthesis on Integer Linear Programming-based approaches, which can be computationally expensive for complex PN structures.


Roshanak Khaleghi received her B.Sc. and M.Sc. degrees both in Industrial and Systems Engineering from University of Tehran, Tehran, Iran. She graduated with her Ph.D. in Industrial Engineering (IE) from the University of Illinois at Urbana-Champaign in 2021, with her research focused on Control of Discrete Event Dynamic Systems. She is currently a Senior Data Analyst with Fraser Health Authority (Vancouver, Canada), where she works on analysis of hospitals’ data (Inpatient and Emergency Department) to help with providing insight on operational and clinical metrics, facilitating data-driven decision making, and improving patient flow and patient/provider outcomes. With her work experience in a complex healthcare system, she is eager to leverage her real-world learnings to inspire and educate the next generation of industrial engineers and is excited about the opportunity of bringing back her industry experiences to higher education, where she can foster a learning environment that encourages innovation, critical thinking, and practical application of engineering principles in healthcare and other domains.

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