Control Of Discrete Event Systems Research Articles

Supervisory Control of Time-Interval Discrete Event Systems

Supervisory Control of Time-Interval Discrete Event Systems

Control of Discrete Event Systems by Using Symbolic Transition Model: An Application to Power Grids

AbstractIn this paper, a new symbolic modeling framework is proposed for the control of discrete event systems (discrete controller synthesis). Reactive infinite-state systems are generally dynamic systems with inputs and outputs. Modeling the outputs in existing symbolic modeling methods for reactive infinite-state systems has not been extensively discussed in the literature. It is crucial to realistically model the outputs and obtain reliable controllers. One of the main contributions and innovations in this study is the ability to symbolically model their output. In this direction, symbolic transition models are offered, where events are defined as guarded symbolic transitions. The framework considers input/output reactive infinite-state systems to satisfy safety and optimization objectives. Effective algorithms and safety control policies are offered to solve the safety control problem (i.e., satisfy the safety objective) for input/output infinite-state systems. Another contribution in this work provides optimization targets within a given cost function based on state transitions, without specifying the target states. The framework is then applied to power grids to demonstrate the effectiveness of the symbolic transition models and experimentally evaluate the new control algorithms. The results showed that the approach is very effective compared to other approaches found in the literature. The computation times required to achieve both safety and optimization objectives are obtained relatively quickly compared to other deterministic methods found in the literature.

Information control in networked discrete event systems

How to control information exchange among different users is an important problem in networked systems with many users/agents. Generally speaking, there are several considerations in control of information exchange in a networked system, including (1) to ensure a friend user has sufficient information to perform its tasks, (2) to deprive an adversary user its information to perform its tasks, (3) to minimize information exchange among friend users so that the risk of information leaking is minimized, and (4) to maximize information broadcasted to all users to achieve maximum transparency. In this paper, we investigate the information control problems in the framework of discrete event systems. Based on the problem at hand, we divide users in a networked system into two or more groups. Users in the same group are consider as friends and users in a different group are consider as adversaries. Several information control problems are investigated and solved using a systematic and rigorous approach. Methods are developed to design controllers that send minimum information to its friends to help them to perform their tasks and broadcast maximum information without helping its adversaries.

Optimal supervisory control of discrete event systems for cyclic tasks

In this paper, we investigate the problem of optimal supervisory control for cyclic tasks in the context of discrete-event systems (DES). We consider the completion of each single task as the visit of a marked state, and overall control objective is to complete tasks cyclically in the sense that marked states are visited infinitely often. Following the standard optimal supervisory control framework, two types of costs, disable cost and occurrence cost, are considered. However, instead of considering the standard accumulated total cost or the average cost per event, we consider the measure for the control performance using the average cost per task. We show that such an optimality measure is more suitable for tasks that need to be completed cyclically. Our goal is to design a live and non-blocking supervisor such that the average cost per task in the worst-case is minimized. To solve the problem, we propose a game-theoretical approach by converting the optimal control problem as a two-player graph game. Structural properties of the converted game are discussed. In particular, we show that this game can be solved by a set of mean payoff decision problems, for which effective algorithms exist. Our problem can be considered as a special instance of the general ratio-game in the literature. However, by exploring new structural property for this problem, we achieve superior computational efficiency when compared to the conventional solution designed for more general problem formulations. Illustrative examples are provided to demonstrate the proposed algorithm.

Optimal Opacity-Enforcing Supervisory Control of Discrete Event Systems on Choosing Cost

To ensure opacity, it is optimal to retain as many as possible occurring event sequences. Contrary to this problem, the other optimal goal is to preserve the minimal occurring event sequences. Based on the choosing cost, an optimal opacity-enforcing problem with minimal discount choosing cost is presented under two constraints in this paper. The first constraint is the opacity of the controlled system. The second is the retention of the secret to the maximum. To solve the model, two scenarios on opacity are considered. For the two scenarios, some algorithms are presented to achieve the optimal solution for the model by using the method of dynamic programming. Then, the solutions produced by the algorithms are proved to be correct by theoretical proof. Finally, some illustrations and an application example on location privacy protection for the algorithms are given.

Supervisory Control of Discrete Event Systems With Dynamic Control Specifications by Petri Nets

Supervisory Control of Discrete Event Systems With Dynamic Control Specifications by Petri Nets

Supervisory control of quantitative Petri nets for fixed‐initial‐credit energy problems using a game structure

AbstractThis work investigates quantitative supervisory control of discrete event systems modeled with Petri nets under the fixed‐initial‐credit energy objective. A weight function referred to as an energy function is defined on a Petri net to characterize the energy level of a transition. The proposed fixed‐initial‐credit energy problem aims to design a supervisor such that the energy level of a transition sequence in a supervised system is higher than 0 under a given initial energy level. The problem is eventually transformed into a two‐player game between a system and a supervisor; supervisor synthesis is reduced to finding a winning strategy in the two‐player game. Instead of enumerating the complete state space of the underlying Petri net, two information structures are utilized, namely the conventional basis reachability graph and the newly proposed essential marking graph, to construct two‐player games based on each of them. It is shown that a winning strategy for a supervisor decoded from the game based on the basis reachability graph of the Petri net is a solution to the problem but is in general restrictive. Further, it is shown that the set of strategies for a supervisor in the game based on the essential marking graph is consistent with that from the game based on the reachability graph of a Petri net. The two developed approaches do not require an exhaustive exploration of the state space of a plant, thus achieving higher efficiency.

A General Architecture for Intersection-Based Decentralized Supervisory Control of Discrete Event Systems

A General Architecture for Intersection-Based Decentralized Supervisory Control of Discrete Event Systems

Hierarchical Supervisory Control Under Partial Observation: Normality

Conditions preserving observability of specifications between the plant and its abstraction are essential for hierarchical supervisory control of discrete-event systems under partial observation. Observation consistency and local observation consistency were identified as such conditions. To preserve normality, only observation consistency is required. Although observation consistency preserves normality between the levels for normal specifications, for specifications that are not normal, observation consistency is insufficient to guarantee that the supremal normal sublanguage computed on the low level and on the high level coincide. We define modified observation consistency, under which the supremal normal sublanguages of different levels coincide. We show that the verification of (modified) observation consistency is <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">PSpace</small> -hard for finite automata and undecidable for slightly more expressive models than finite automata. Decidability of (modified) observation consistency is an open problem. Hence we further discuss two stronger conditions that are easy to verify. Finally, we illustrate the conditions on an example of a railroad controller and on a case study of a part of an MRI scanner.

Sensor deception attacks against security in supervisory control systems

This paper investigates the problem of synthesizing sensor deception attacks against security in the context of supervisory control of discrete-event systems (DES). We consider a DES plant controlled by a supervisor, whose security requirement is to maintain the initial-secret of the system undetected, i.e., it does not want to reveal the fact that it was initiated from a secret state. On the other hand, there exists an active attacker that can tamper with the observations received by the supervisor by, e.g., hacking into the communication channel between the sensors and the supervisor. The objective of the attacker is to deceive the supervisor such that the initial-secret is revealed due to incorrect control actions. We investigate the problem from the attacker’s point of view and focus on synthesizing attack strategies that threaten the security of the system. We consider two levels of success of the attacker: one requires that the attacker can detect the initial-secret of the system “almost surely” and the other only requires that the attacker has the possibility to detect the initial-secret of the system. For both cases, we present algorithms for synthesizing successful attack strategies. Our approach is based on the All Attack Structure (AAS) which records state estimates for both the supervisor and the attacker. Structural properties of the security requirements are also leveraged to reduce the synthesis complexity. A running academic example is provided to illustrate the proposed synthesis procedures.

Smart Platform for Monitoring and Control of Discrete Event System in Industry 4.0 Concept

We are now living in a time when the fourth industrial revolution is bringing new technologies with intensive digitalization of all levels of production. This paper presents a complex solution for the monitoring, diagnosis, and control of the production process, in our case, discrete event systems. The proposed solution—a mechatronic platform—further develops and extends our recent results where the overall concept was outlined and some partial tasks were studied. The present paper provides the complete structure of the proposed platform together with implementation details for all functionalities. The developed platform uses the latest technologies, such as OPC UA; industrial communication and visualization protocols and tools; and augmented reality, which enables comfortable interaction with real processes. The laboratory-scaled case study shows the qualities of the proposed solution.

A New Approach for Verification of Delay Co-observability of Discrete-Event Systems

In decentralized networked supervisory control of discrete-event systems (DESs), the local supervisors observe event occurrences subject to observation delays to make correct control decisions. Delay coobservability describes whether these local supervisors can make sufficient observations. In this paper, we provide an efficient way to verify delay coobservability. For each controllable event, we partition the specification language into a finite number of sets such that strings in different sets have different lengths. For each of the sets, we construct a verifier to check if delay coobservability holds for the controllable event. The computational complexity of the proposed approach is polynomial with respect to the number of states, the number of events, and the upper bounds on observation delays and only exponential with respect to the number of local supervisors. It has lower complexity order than the existing approaches. In addition, we investigate the relationship between the decentralized supervisory control of networked DESs and the decentralized fault diagnosis of networked DESs and show that delay <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> -codiagnosability is transformable to delay coobservability. Thus, techniques for the verification of delay coobservability can be leveraged to verify delay <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> -codiagnosability.

Supervisory Control of Fuzzy Discrete Event Systems Under Partial Observation

Supervisory control of fuzzy discrete event systems under partial observation is investigated in the paper. Without loss of generality, we consider fuzzy discrete event systems with constraints where a fuzzy discrete event system is modeled by a fuzzy automaton. Sequences of events that can be generated by the system are regarded as constraints and are modeled by a crisp automaton. A supervisor is designed to control the fuzzy discrete event system so that the supervised system is prevented from entering a pre-specified set of illegal/unsafe fuzzy states. A necessary and sufficient condition for the existence of a supervisor is obtained. When the condition is satisfied, an online supervisor can be designed. Fuzzy state estimation problem is first solved, as the supervisor is fuzzy-state-estimate-based. A method is developed to estimate fuzzy state iteratively after observation of each new event. We show that the supervisor so developed ensures the safety of the system and is least restrictive among all possible safe supervisors. Potential of the theoretical results for real-world applications is illustrated through an example of HIV/AIDS treatment decision-making.

A survey on compositional algorithms for verification and synthesis in supervisory control

AbstractThis survey gives an overview of the current research on compositional algorithms for verification and synthesis of modular systems modelled as interacting finite-state machines. Compositional algorithms operate by repeatedly simplifying individual components of a large system, replacing them by smaller so-called abstractions, while preserving critical properties. In this way, the exponential growth of the state space can be limited, making it possible to analyse much bigger state spaces than possible by standard state space exploration. This paper gives an introduction to the principles underlying compositional methods, followed by a survey of algorithmic solutions from the recent literature that use compositional methods to analyse systems automatically. The focus is on applications in supervisory control of discrete event systems, particularly on methods that verify critical properties or synthesise controllable and nonblocking supervisors.

Language Recovery in Discrete-Event Systems against Sensor Deception Attacks

Cyber-physical systems are characterized by the intrinsic combination of software and physical components that usually include (wired and wireless) communication devices, sensors, actuators, and control processing units. Some wireless devices communicate over insecure channels, rendering cyber-physical systems at risk of malicious attacks that might lead to catastrophic damage. This paper touches upon the problem of sensor deception attacks in supervisory control of discrete-event systems, where an attacker can insert, delete, or replace sensor readings to mislead the supervisor and induce system damage. We model potential attacks using nondeterministic finite-state transducers and then introduce a new defence strategy that utilizes insertion functions. Insertion functions are a type of monitoring interface that alters the system’s behaviour by adding extra observable events. Finally, we construct a nondeterministic finite-state transducer called a supervisor filter that recovers the original language generated by the plant by handling the altered language. The insertion function and the supervisor filter cooperate to control the system and confuse the intruder without confusing the supervisor.

Detection of Actuator Enablement Attacks by Petri Nets in Supervisory Control Systems

The feedback control system with network-connected components is vulnerable to cyberattacks. We study a problem of attack detection in supervisory control of discrete-event systems. The scenario of a system subjected to actuator enablement attacks is considered in this article. We also consider that some unsafe places that should be protected from an attacker exist in the system, and some controllable events that are disabled by a supervisor might be re-enabled by an attacker. This article proposes a defense strategy to detect actuator enablement attacks and disable all controllable events after detecting an attack. We design algorithmic procedures to determine whether the system can be protected against damage caused by actuator enablement attacks, where the damage is predefined as a set of “unsafe” places. In this way, the system property is called “AE-safe controllability”. The safe controllability can be verified by using a basis diagnoser or a basis verifier. Finally, we explain the approach with a cargo system example.

ИНТЕЛЛЕКТУАЛЬНОЕ ПЛАНИРОВАНИЕ СТРАТЕГИЙ И УПРАВЛЕНИЕ ГРУППОЙ МОБИЛЬНЫХ РОБОТОВ В УСЛОВИЯХ НЕПОЛНОТЫ ИНФОРМАЦИИ

Different problems of strategy planning and control of a mobile robot group under complex dynamicconditions with incomplete information about the external environment are considered. Approachesto solving problems of effective work scheduling under conditions of inconstant active groupcomposition, searching for the source of a nonstationary concentration field, supervisory control ofdiscrete-event systems are presented. An original mathematical model formulated in terms of work-shiftscheduling problems and a problem-oriented modification of evolutionary algorithms with a specializedset of heuristics for its efficient solution are developed for the problem of scheduling top-level groupwork. Searching and monitoring the source of the nonstationary concentration field is carried out usinga decentralized multi-agent control strategy that combines elements of bionic and gradient approaches,as well as a method for generating artificial potential fields. The considered control strategy has lowcomputational complexity, high variability with respect to the types of fields surveyed, and is easily scalableto control any available number of mobile robots. The latter is of special importance, in particularwhen considering the problem of parallel and independent monitoring of multiple sources. It is proposedto use the means of logical inference, namely automatic theorem proving in the calculus of positivelyconstructed formulas, to solve various problems of the supervised control theory of discrete-eventsystems used at different levels of the robotic complex hierarchical control system. Features of the calculusallows solving complex problems of dynamic systems control, as well as processing and controllingevents based on environmental data in real time in the process of logical inference efficiently. Theapproach based on positively constructed formulas allows studying the properties of automata-baseddiscrete-event systems, as well as to synthesize and model finite automata for the construction and realizationof monolithic and modular supervisors. A general scheme combining the considered approachesfor controlling a group of mobile robots at different levels and time scales within a single hierarchicalcontrol system is proposed.

MDESops: An Open-Source Software Tool for Discrete Event Systems Modeled by Automata

The salient features of the new software tool MDESops are presented. MDESops is Python-based and open-source. Its focus is the analysis and control of discrete event systems (DES) modeled by finite-state automata. MDESops has core functions to manipulate deterministic and nondeterministic automata, including parallel composition and determinization. It has functions to analyze diagnosability and opacity properties. MDESops also includes functions that implement both standard and more recent algorithmic procedures from the theory of supervisory control of DES, including synthesis of supervisors for partially-observed systems, synthesis of attackers in systems with compromised sensors, and synthesis of supervisors resilient to deception attacks. It is the hope that MDESops can serve as a useful platform for algorithm development and prototyping in DES research.

Reducing the Learning Time of Reinforcement Learning for the Supervisory Control of Discrete Event Systems

Reducing the Learning Time of Reinforcement Learning for the Supervisory Control of Discrete Event Systems

UltraDES Project - A Multiplatform Discrete Event Systems Tool*

In this paper we present the UltraDES Project, composed of the UltraDES library, as well as a wrapper to Python and a Web Application. UltraDES is an open source project, available at https://github.com/lacsed/UltraDES. It has several functions and data structures for analysis and control of Discrete Event Systems and is under development since 2013. Currently, a new set of algorithms were implemented in the context of Supervisory Control Theory, but also some basic functions for Petri nets.