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 337 articles )

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  1. Chen, Rui; Cassandras, Christos G.: Stochastic flow models with delays, blocking and applications to multi-intersection traffic light control (2020)
  2. Nozari, Erfan; Tallapragada, Pavankumar; Cortés, Jorge: Event-triggered stabilization of nonlinear systems with time-varying sensing and actuation delay (2020)
  3. Reveliotis, Spyros: On the state liveness of some classes of guidepath-based transport systems and its computational complexity (2020)
  4. Yang, Jung-Min: Coordinated static control of asynchronous sequential machines (2020)
  5. Zhang, Zhipeng; Xia, Chengyi; Chen, Zengqiang: On the stabilization of nondeterministic finite automata via static output feedback (2020)
  6. Abbasi, Rosa; Ghassemi, Fatemeh; Khosravi, Ramtin: Verification of asynchronous systems with an unspecified component (2019)
  7. Atampore, Francis; Dingel, Juergen; Rudie, Karen: A controller synthesis framework for automated service composition (2019)
  8. Bolzern, Paolo; Colaneri, Patrizio; De Nicolao, Giuseppe: Opinion influence and evolution in social networks: a Markovian agents model (2019)
  9. Daugherty, Greyson; Reveliotis, Spyros; Mohler, Greg: Efficient generation of performance bounds for a class of traffic scheduling problems (2019)
  10. Hagebring, Fredrik; Lennartson, Bengt: Time-optimal control of large-scale systems of systems using compositional optimization (2019)
  11. Masopust, Tomáš; Yin, Xiang: Complexity of detectability, opacity and A-diagnosability for modular discrete event systems (2019)
  12. Moreira, Marcos V.; Lesage, Jean-Jacques: Discrete event system identification with the aim of fault detection (2019)
  13. Pola, Giordano; Di Benedetto, Maria Domenica; Borri, Alessandro: Symbolic control design of nonlinear systems with outputs (2019)
  14. Poveda, Jorge I.; Benosman, Mouhacine; Teel, Andrew R.: Hybrid online learning control in networked multiagent systems: A survey (2019)
  15. Shamsizadeh, Marzieh; Zahedi, Mohammad Mehdi: Bisimulation of type 2 for BL-general fuzzy automata (2019)
  16. Viana, Gustavo S.; Basilio, João C.: Codiagnosability of discrete event systems revisited: a new necessary and sufficient condition and its applications (2019)
  17. Wakaiki, Masashi; Tabuada, Paulo; Hespanha, João P.: Supervisory control of discrete-event systems under attacks (2019)
  18. Wang, Biao; Feng, Jun-e; Meng, Min: Matrix approach to detectability of discrete event systems (2019)
  19. Yin, Xiang; Lafortune, Stéphane: A general approach for optimizing dynamic sensor activation for discrete event systems (2019)
  20. Yin, Xiang; Li, Zhaojian; Wang, Weilin; Li, Shaoyuan: Infinite-step opacity and (K)-step opacity of stochastic discrete-event systems (2019)

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