CPL - Chalmers Publication Library
| Utbildning | Forskning | Styrkeområden | Om Chalmers | In English In English Ej inloggad.

Solving Two Supervisory Control Benchmark Problems Using Supremica

Sajed Miremadi (Institutionen för signaler och system, Automation) ; Knut Åkesson (Institutionen för signaler och system, Automation) ; Martin Fabian (Institutionen för signaler och system, Automation) ; Arash Vahidi (Institutionen för signaler och system, Automation) ; Bengt Lennartson (Institutionen för signaler och system, Automation)
9th International Workshop on Discrete Event Systems, 2008 p. 131-136. (2008)
[Konferensbidrag, refereegranskat]

Two supervisory control benchmark problems for WODES'08 are solved using the tool Supremica. Supremica is a tool for formal synthesis of discrete-event control functions based on discrete event models of the uncontrolled plant and specifications of the desired closed-loop behavior. By using formal synthesis of control functions the need for formal verification is reduced since the control functions are computed to automatically fulfill the given specifications, that is, they are "correct by construction". The modeling framework in Supremica is based on finite automata. Supremica implements several techniques for being able to solve large scale problems. In this paper it is evaluated how the algorithms implemented in Supremica that are based on binary decision diagrams performs on the two benchmark problems. The two benchmark problems are generalization of two classical problems; cat and mouse, and the dining philosophers' problem. The benchmark problems are parametrized such that it is possible to create problem instances with huge state-spaces. The benchmark shows that Supremica can efficiently solve rather large problem instances.

Denna post skapades 2008-11-20. Senast ändrad 2016-02-01.
CPL Pubid: 78497


Läs direkt!

Lokal fulltext (fritt tillgänglig)

Länk till annan sajt (kan kräva inloggning)

Institutioner (Chalmers)

Institutionen för signaler och system, Automation


Datavetenskap (datalogi)

Chalmers infrastruktur