Object-Oriented Implementation of the minimally restrictive liveness enforcing supervisory policy in a class of Petri nets
Chandrasekaran, Sangeetha
Loading…
Permalink
https://hdl.handle.net/2142/42202
Description
Title
Object-Oriented Implementation of the minimally restrictive liveness enforcing supervisory policy in a class of Petri nets
Author(s)
Chandrasekaran, Sangeetha
Issue Date
2013-02-03T19:27:44Z
Director of Research (if dissertation) or Advisor (if thesis)
Sreenivas, Ramavarapu S.
Department of Study
Industrial&Enterprise Sys Eng
Discipline
Industrial Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Controlled Petri nets
Supervisory policy for discrete systems
Liveness
livelock avoidance
Control invariance
Minimally restrictive
Abstract
Livelock avoidance is an essential requirement in Discrete-Event/Discrete-State (DEDS) systems. Every
event of a live DEDS system can be executed at some instant in the future, irrespective of its past activities.
When a DEDS system is in a livelock-state, some events will enter into a state of suspended animation
for perpetuity, while others proceed with no impediment. This report is about the automatic synthesis of
Liveness Enforcing Supervisory Policies (LESPs) for Petri net models of DEDS systems.
Past research has shown that the existence of an LESP in DEDS systems modeled by a class of general
Free-Choice Petri Nets (FCPNs) is decidable, and the minimally restrictive LESP is directly related to the
presence of a right-closed set of states that are control invariant with respect to the system. A minimally
restrictive LESP prevents the occurrence of events in a DEDS system only when it is absolutely necessary.
This study describes an object-oriented implementation of the minimally restrictive supervisory policy for a
class of Petri nets for which this policy is decidable.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.