We consider a reliable decentralized supervisory control problem for discrete event systems in the inference-based framework. This problem requires us to synthesize local supervisors such that the controlled system achieves the specification and is nonblocking, even if local control decisions of some local supervisors are not available for making the global control decision. In the case of single-level inference, we introduce a notion of reliable 1-inference-observability and show that reliable 1-inference-observability together with controllability and Lm(G)-closedness is a necessary and sufficient condition for the existence of a solution to the reliable decentralized supervisory control problem.

Blockchain is a distributed ledger technology for recording transactions. When two or more miners create different versions of the blocks at almost the same time, blockchain forks occur. We model the mining process with forks by a discrete event system and design a supervisor controlling these forks.

We consider the bisimilarity control problem for partially observed nondeterministic discrete event systems with deterministic specifications. This problem requires us to synthesize a supervisor that achieves bisimulation equivalence of the supervised system and the deterministic specification under partial observation. We present necessary and sufficient conditions for the existence of such a deterministic supervisor and show that these conditions can be verified polynomially.

In this letter, we propose a more secure modeling and simulation approach that can systematically detect state variable corruptions caused by buffer overflows in simulation models. Using our approach, developers may not consider secure coding practices related to the corruptions. We have implemented a prototype of the approach based on a modeling and simulation formalism and an open source simulator. Through optimization, the prototype could show better performance, compared to the original simulator, and detect state variable corruptions.

In this paper, we introduce conditional decisions for enforcing forcible events in the decentralized supervisory control framework for timed discrete event systems. We first present sufficient conditions for the existence of a decentralized supervisor with conditional decisions. These sufficient conditions are weaker than the necessary and sufficient conditions for the existence of a decentralized supervisor without conditional decisions. We next show that the presented sufficient conditions are also necessary under the assumption that if the occurrence of the event tick, which represents the passage of one time unit, is illegal, then a legal forcible event that should be forced to occur uniquely exists. In addition, we develop a method for verifying the presented conditions under the same assumption.

We consider a similarity control problem for discrete event systems modeled as nondeterministic automata. A nonblocking supervisor was synthesized in the previous work under the assumption that the event occurrence and the current state of the plant are observable. In this letter, we prove that the synthesized supervisor is a maximally permissive nonblocking one.

In this paper, we study a control problem of a concurrent discrete event system, where several subsystems are partially synchronized via shared events, under local and global constraints described by linear temporal logic formulas. We propose a hierarchical control architecture consisting of local supervisors and a coordinator. While the supervisors ensure the local requirements, the coordinator decides which shared events to be disabled so as to satisfy the global specification. First, we construct Rabin games to obtain local supervisors. Next, we reduce them based on shared transitions. Finally, we construct a global Rabin game from the reduced supervisors and a deterministic Rabin automaton that accepts every run satisfying the global specification. By solving it, we obtain a coordinator that disables shared events to guarantee the global requirement. Moreover, the concurrent system controlled by the coordinator and the local supervisors is deadlock-free.

In this paper, we consider a similarity control problem for nondeterministic discrete event systems, which requires us to synthesize a nonblocking supervisor such that the supervised plant is simulated by a given specification. We assume that a supervisor can observe not only the event occurrence but also the current state of the plant. We present a necessary and sufficient condition for the existence of a nonblocking supervisor that solves the similarity control problem and show how to verify it in polynomial time. Moreover, when the existence condition of a nonblocking supervisor is satisfied, we synthesize such a supervisor as a solution to the similarity control problem.

This paper studies the supervisory control of partially observed quantitative discrete event systems (DESs) under the fixed-initial-credit energy objective. A quantitative DES is modeled by a weighted automaton whose event set is partitioned into a controllable event set and an uncontrollable event set. Partial observation is modeled by a mapping from each event and state of the DES to the corresponding masked event and masked state that are observed by a supervisor. The supervisor controls the DES by disabling or enabling any controllable event for the current state of the DES, based on the observed sequences of masked states and masked events. We model the control process as a two-player game played between the supervisor and the DES. The DES aims to execute the events so that its energy level drops below zero, while the supervisor aims to maintain the energy level above zero. We show that the proposed problem is reducible to finding a winning strategy in a turn-based reachability game.

We consider a decentralized similarity control problem for composite nondeterministic discrete event systems, where each subsystem has its own local specification and the entire specification is described as the synchronous composition of local specifications. We present necessary and sufficient conditions for the existence of a complete decentralized supervisor that solves a similarity control problem under the assumption that any locally uncontrollable event is not shared by other subsystems. We also show that the system controlled by the complete decentralized supervisor that consists of maximally permissive local supervisors is bisimilar to the one controlled by the maximally permissive monolithic supervisor under the same assumption.

This paper considers an optimal stabilization problem of quantitative discrete event systems (DESs) under the influence of disturbances. We model a DES by a deterministic weighted automaton. The control cost is concerned with the sum of the weights along the generated trajectories reaching the target state. The region of weak attraction is the set of states of the system such that all trajectories starting from them can be controlled to reach a specified set of target states and stay there indefinitely. An optimal stabilizing controller is a controller that drives the states in this region to the set of target states with minimum control cost and keeps them there. We consider two control objectives: to minimize the worst-case control cost (1) subject to all enabled trajectories and (2) subject to the enabled trajectories starting by controllable events. Moreover, we consider the disturbances which are uncontrollable events that rarely occur in the real system but may degrade the control performance when they occur. We propose a linearithmic time algorithm for the synthesis of an optimal stabilizing controller which is robust to disturbances.

In previous papers by the authors, a new scheme for diagnosis of stochastic discrete event systems, called sequence profiling (SP), is proposed. From given event logs, N-gram models that approximate the behavior of the target system are extracted. N-gram models are used for discovering discrepancy between observed event logs and the behavior of the system in the normal situation. However, when the target system is a distributed system consisting of several subsystems, event sequences from subsystems may be interleaved, and SP cannot separate the faulty event sequence from the interleaved sequence. In this paper, we introduce wildcard characters into event patterns. This contributes to removing the effect by subsystems which may not be related to faults.

In this paper, we present a new method for diagnosis of stochastic discrete event system. The method is based on anomaly detection for sequences. We call the method sequence profiling (SP). SP does not require any system models and any system-specific knowledge. The only information necessary for SP is event logs from the target system. Using event logs from the system in the normal situation, N-gram models are learned, where the N-gram model is used as approximation of the system behavior. Based on the N-gram model, the diagnoser estimates what kind of faults has occurred in the system, or may conclude that no faults occurs. Effectiveness of the proposed method is demonstrated by application to diagnosis of a multi-processor system.

In this paper, we consider a decentralized failure diagnosis problem for discrete event systems. For a conjunctively codiagnosable system, there exists a conjunctive decentralized diagnoser that can detect the occurrence of any failure within a uniformly bounded number of steps. We present a method for synthesizing such a conjunctive decentralized diagnoser as an online diagnoser.

In this paper, we consider a similarity control problem for plants and specifications, modeled as nondeterministic automata. This problem requires us to synthesize a nondeterministic supervisor such that the supervised plant is simulated by a given specification. We assume that a supervisor can observe not only the event occurrence but also the current state of the plant. First, we derive a necessary and sufficient condition for the existence of a complete supervisor, which is a solution to the similarity control problem. Then, we present a method for synthesizing a maximally permissive similarity enforcing supervisor when the existence condition is satisfied.

In this paper, we study conjunctive decentralized diagnosis of discrete event systems (DESs). In most existing works on decentralized diagnosis of DESs, it is implicitly assumed that diagnosis decisions of all local diagnosers are available to detect a failure. However, it may be possible that some local diagnosis decisions are not available, due to some reasons. Letting n be the number of local diagnosers, the notion of (n,k)-conjunctive codiagnosability guarantees that the occurrence of any failure is detected in the conjunctive architecture as long as at least k of the n local diagnosis decisions are available. We propose an algorithm for verifying (n,k)-conjunctive codiagnosability. To construct a reliable conjunctive decentralized diagnoser, we need to compute the delay bound within which the occurrence of any failure can be detected as long as at least k of the n local diagnosis decisions are available. We show how to compute the delay bound.

For a fixed number of nodes, we focus on directed acyclic graphs in which there is not a shortcut. We find the case where the number of paths is maximized and its corresponding count of maximal paths. Considering this case is essential in solving large-scale scheduling problems using a PERT chart.

In this paper, we study a supervisory control problem for plants and specifications modeled by nondeterministic automata. This problem requires to synthesize a nondeterministic supervisor such that the supervised plant is bisimilar to a given specification. We assume that a supervisor can observe not only the event occurrence but also the current state of the plant, and introduce a notion of completeness of a supervisor which guarantees that all nondeterministic transitions caused by events enabled by the supervisor are defined in the supervised plant. We define a notion of partial bisimulation between a given specification and the plant, and prove that it serves as a necessary and sufficient condition for the existence of a bisimilarity enforcing complete supervisor.

In this paper, we study decentralized supervisory control of timed discrete event systems, where we adopt the OR rule for fusing local enablement decisions and the AND rule for fusing local enforcement decisions. For any specification language satisfying a certain assumption, we propose a method for constructing a decentralized supervisor that achieves its sublanguage. The proposed method does not require computing the achieved sublanguage.

In this paper, we propose an optimal supervisory control method for discrete event systems (DESs) that have different preferences. In our previous work, we proposed an optimal supervisory control method based on reinforcement learning. In this paper, we extend it and consider a system that consists of several local systems. This system is modeled by a decentralized DES (DDES) that consists of local DESs, and is supervised by a central supervisor. In addition, we consider that the supervisor and each local DES have their own preferences. Each preference is represented by a preference function. We introduce the new value function based on the preference functions. Then, we propose the learning method of the optimal supervisor based on reinforcement learning for the DDESs. The supervisor learns how to assign the control pattern so as to maximize the value function for the DDES. The proposed method shows the general framework of optimal supervisory control for the DDES that consists of several local systems with different preferences. We show the efficiency of the proposed method through a computer simulation.