A hierarchical decomposition of decision process Petri nets for modeling complex systems

• Autorzy: Clempner J.
• Języki publikacji: EN

Abstrakty

EN

We provide a framework for hierarchical specification called Hierarchical Decision Process Petri Nets (HDPPNs). It is an extension of Decision Process Petri Nets (DPPNs) including a hierarchical decomposition process that generates less complex nets with equivalent behavior. As a result, the complexity of the analysis for a sophisticated system is drastically reduced. In the HDPPN, we represent the mark-dynamic and trajectory-dynamic properties of a DPPN. Within the framework of the mark-dynamic properties, we show that the HDPPN theoretic notions of (local and global) equilibrium and stability are those of the DPPN. As a result in the trajectory-dynamic properties framework, we obtain equivalent characterizations of that of the DPPN for final decision points and stability. We show that the HDPPN mark-dynamic and trajectory-dynamic properties of equilibrium, stability and final decision points coincide under some restrictions. We propose an algorithm for optimum hierarchical trajectory planning. The hierarchical decomposition process is presented under a formal treatment and is illustrated with application examples.

Słowa kluczowe

EN

hierarchy; decomposition; structuring mechanisms; re-usable components; decision process; DPPN; stability; Lyapunov methods; optimization

PL

hierarchia; rozkład; składnik wielokrotnego użycia; proces decyzyjny; stabilność; optymalizacja; metoda Lyapunova; DPPN

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2010
• Tom: Vol. 20, no 2
• Strony: 349--366
• Opis fizyczny: Bibliogr. 18 poz., rys., tab.

Twórcy

autor

Clempner J.

• Center for Computing Research National Polytechnic Institute (CIC-IP), Av. Juan de Dios Batiz s/n, Edificio CIC, Col. Nueva Industrial Vallejo 07738 Mexico City, Mexico

Bibliografia

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