Minimization of fuzzy finite automata
Information Sciences: an International Journal
Information Sciences: an International Journal - Intelligent manufacturing and fault diagnosis (II). Soft computing approaches to fault diagnosis
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Determinism and fuzzy automata
Information Sciences—Informatics and Computer Science: An International Journal
A Framework of Fuzzy Diagnosis
IEEE Transactions on Knowledge and Data Engineering
Introduction to Discrete Event Systems
Introduction to Discrete Event Systems
Fault diagnosis in discrete time hybrid systems - A case study
Information Sciences: an International Journal
Minimization of states in automata theory based on finite lattice-ordered monoids
Information Sciences: an International Journal
Decision making in fuzzy discrete event systems
Information Sciences: an International Journal
The relationships among several types of fuzzy automata
Information Sciences: an International Journal
Combining uncertainty and imprecision in models of medical diagnosis
Information Sciences: an International Journal
Three-way two-dimensional alternating finite automata with rotated inputs
Information Sciences: an International Journal
A Fuzzy Discrete Event System Approach to Determining Optimal HIV/AIDS Treatment Regimens
IEEE Transactions on Information Technology in Biomedicine
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modeling and control of fuzzy discrete event systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Supervisory control of fuzzy discrete event systems: a formal approach
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Decentralized failure diagnosis of discrete event systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fuzzy set-based methods in instance-based reasoning
IEEE Transactions on Fuzzy Systems
Observability and decentralized control of fuzzy discrete-event systems
IEEE Transactions on Fuzzy Systems
Fuzzy automata with fuzzy relief
IEEE Transactions on Fuzzy Systems
The relationship of controllability between classical and fuzzy discrete-event systems
Information Sciences: an International Journal
Encoding fuzzy possibilistic diagnostics as a constrained optimization problem
Information Sciences: an International Journal
Fault detection and isolation based on fuzzy automata
Information Sciences: an International Journal
Information Sciences: an International Journal
Diagnosability of fuzzy discrete-event systems: a fuzzy approach
IEEE Transactions on Fuzzy Systems
A new algorithm for testing diagnosability of fuzzy discrete event systems
Information Sciences: an International Journal
From classic observability to a simple fuzzy observability for fuzzy discrete-event systems
Information Sciences: an International Journal
Computation of the greatest simulations and bisimulations between fuzzy automata
Fuzzy Sets and Systems
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In this paper, discrete event systems (DESs) are reformulated as fuzzy discrete event systems (FDESs) and fuzzy discrete event dynamical systems (FDEDSs). These frameworks include fuzzy states, events and IF-THEN rules. In these frameworks, all events occur at the same time with different membership degrees. Fuzzy states and events have been introduced to describe uncertainties that occur often in practical problems, such as fault diagnosis applications. To measure a diagnoser's fault discrimination ability, a fuzzy diagnosability degree is proposed. If the diagnosability of the degree of the system yields one a diagnoser can be implemented to identify all possible fault types related to a system. For any degree less than one, researchers should not devote their time to distinguish all possible fault types correctly. Thus, two different diagnosability definitions FDEDS and FDES are introduced. Due to the specialized fuzzy rule-base embedded in the FDEDS, it is capable of representing a class of non-linear dynamic system. Computationally speaking, the framework of diagnosability of the FDEDS is structurally similar to the framework of diagnosability of a non-linear system. The crisp DES diagnosability has been turned into the term fuzzy diagnosability for the FDES. The newly proposed diagnosability definition allows us to define a degree of diagnosability in a class of non-linear systems. In addition, a simple fuzzy diagnosability checking method is introduced and some numerical examples are provided to illustrate this theoretical development. Finally, the potential applications of the proposed method are discussed.