Discrete Event Systems Modeling and Control

Discrete event systems (DES) are dynamic systems in which state changes occur at distinct instants in response to asynchronously generated events. Modelling and control of such systems rely on formal frameworks—most notably finite automata and Petri nets—to capture both logical behaviour and resource constraints. Over the past decade, research has advanced from foundational questions of liveness and deadlock avoidance towards richer analyses of fault diagnosis, detectability, security and resilience. Supervisor synthesis techniques impose control policies to restrict event sequences, ensuring safety and performance objectives are met without inducing undue conservatism. Extensions such as coloured Petri nets and vector DES allow compact representations of complex manufacturing and logistics processes, while interpreted Petri nets integrate sensor and actuator signals for cyber-physical applications. Recent work also explores encryption of control structures, diagnostic predicates, and observer-based approaches for state estimation under attack. These developments are central to real-time, safety-critical systems in manufacturing, transportation and smart infrastructure, where system integrity and adaptability must be guaranteed under uncertainty, failure and malicious interference.

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Research from all publishers

Recent studies have introduced homomorphic encryption techniques for supervisory control systems modelled as deterministic finite automata. By expressing automata in matrix form, researchers have achieved data encryption schemes that preserve the ability to compute control actions on encrypted data. Entropy-enhancing algorithms conceal matrix entries against brute-force attacks, and corresponding decryption processes restore control commands without compromising system security.

In reconfigurable manufacturing systems, intelligent coloured token Petri nets have emerged to model dynamic modifications such as machine breakdowns, rework and product-type changes. Tokens carry real-time knowledge regarding system status, enabling modular updates to the net structure when configurations change. This approach guarantees deadlock-free, conservative and reversible behaviour, while substantially reducing model complexity and supporting rapid reconfiguration in response to market fluctuations.

Work on detectability within labelled Petri nets and finite automata has clarified the computational limits of state reconstruction from output observations. New notions of eventual strong detectability have been formalised, showing decidability under mild assumptions for Petri nets and polynomial-time verification for automata. These results delineate when an observer can reliably determine the current state after a finite observation prefix, providing crucial insight for the design of monitoring and fault-tolerant controllers.

Discrete Event Systems Modeling and Control publication trend

The graph below shows the total number of articles in discrete event systems modeling and control across all publications each year (not limited to Nature Index journals).

Technical terms

Discrete event system: A system whose state evolution is driven by the occurrence of discrete events rather than by continuous time dynamics.

Petri net: A bipartite graph formalism comprising places, transitions and tokens, used to model concurrent and synchronised processes.

Finite automaton: A mathematical model of computation with a finite set of states and transitions triggered by events or symbols.

Supervisor synthesis: The process of designing a control policy that restricts the behaviour of a DES to satisfy safety and liveness specifications.

Deadlock: A system state in which no further progress is possible because required resources are mutually blocked.

Detectability: The property that an observer can infer the current system state from a sequence of observed outputs after a finite delay.

Coloured Petri net: An extension of Petri nets in which tokens carry data values (“colours”), allowing more compact and expressive models of complex systems.

References

1. Homomorphic Encryption of Supervisory Control Systems Using Automata. IEEE Access (2020).
2. Intelligent Colored Token Petri Nets for Modeling, Control, and Validation of Dynamic Changes in Reconfigurable Manufacturing Systems. Processes (2020).
3. On detectability of labeled Petri nets and finite automata. Discrete Event Dynamic Systems (2020).
4. Determinism in Cyber-Physical Systems Specified by Interpreted Petri Nets. Sensors (2020).
5. Diagnosability of Vector Discrete-Event Systems Using Predicates. IEEE Access (2019).
6. Joint State Estimation Under Attack of Discrete Event Systems. IEEE Access (2021).