UMDES

UMDES Software Library: UMDES-LIB is a library of C routines written for the study of discrete event systems modeled by finite-state automata (FSA). There are routines for the manipulation of FSA’s, routines that implement many of the operations of supervisory control theory, and routines that implement the methodology developed at University of Michigan for failure diagnosis of discrete event systems. The book ”Introduction to Discrete Event Systems” by Christos G. Cassandras and Stéphane Lafortune may be consulted for an introduction to modeling of discrete event systems by FSA’s, manipulation of FSA models, and the theory of supervisory control of discrete event systems.


References in zbMATH (referenced in 239 articles )

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  1. Ammour, Rabah; Leclercq, Edouard; Sanlaville, Eric; Lefebvre, Dimitri: Fault prognosis of timed stochastic discrete event systems with bounded estimation error (2017)
  2. Behrisch, Mike; Kerkhoff, Sebastian; Pöschel, Reinhard; Schneider, Friedrich Martin; Siegmund, Stefan: Dynamical systems in categories (2017)
  3. Dallal, Eric; Colombo, Alessandro; Del Vecchio, Domitilla; Lafortune, Stéphane: Supervisory control for collision avoidance in vehicular networks using discrete event abstractions (2017)
  4. Figueiredo, Daniel; Martins, Manuel A.; Chaves, Madalena: Applying \itdifferential dynamic logic to reconfigurable biological networks (2017)
  5. Fleck, Julia L.; Cassandras, Christos G.: Optimal design of personalized prostate cancer therapy using Infinitesimal Perturbation Analysis (2017)
  6. Haar, Stefan; Haddad, Serge; Melliti, Tarek; Schwoon, Stefan: Optimal constructions for active diagnosis (2017)
  7. Hakizimana, Alphonse; Scott, Joseph K.: Differentiability conditions for stochastic hybrid systems with application to the optimal design of microgrids (2017)
  8. Keroglou, Christoforos; Hadjicostis, Christoforos N.: Verification of detectability in probabilistic finite automata (2017)
  9. Liu, Fuchun; Mo, Rixiang: Correctability of fault-tolerant stochastic discrete-event systems (2017)
  10. Petrosian, Ovanes; Barabanov, Andrey: Looking forward approach in cooperative differential games with uncertain stochastic dynamics (2017)
  11. Pinisetty, Srinivas; Preoteasa, Viorel; Tripakis, Stavros; Jéron, Thierry; Falcone, Yliès; Marchand, Hervé: Predictive runtime enforcement (2017)
  12. Pola, Giordano; De Santis, Elena; Di Benedetto, Maria Domenica; Pezzuti, Davide: Design of decentralized critical observers for networks of finite state machines: a formal method approach (2017)
  13. Santoro, Leonardo P.M.; Moreira, Marcos V.; Basilio, João C.: Computation of minimal diagnosis bases of discrete-event systems using verifiers (2017)
  14. Thorsley, David: A necessary and sufficient condition for diagnosability of stochastic discrete event systems (2017)
  15. van Hulst, A.C.; Reniers, M.A.; Fokkink, W.J.: Maximally permissive controlled system synthesis for non-determinism and modal logic (2017)
  16. Xiao, Hui; Gao, Siyang; Lee, Loo Hay: Simulation budget allocation for simultaneously selecting the best and worst subsets (2017)
  17. Yin, Xiang: Initial-state detectability of stochastic discrete-event systems with probabilistic sensor failures (2017)
  18. Yin, Xiang; Lafortune, Stéphane: Verification complexity of a class of observational properties for modular discrete events systems (2017)
  19. Yin, Xiang; Lafortune, Stéphane: A new approach for the verification of infinite-step and $K$-step opacity using two-way observers (2017)
  20. Yokota, Shoichi; Yamamoto, Takashi; Takai, Shigemasa: Computation of the delay bounds and synthesis of diagnosers for decentralized diagnosis with conditional decisions (2017)

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