Abstract:This paper describes networked discrete-event systems as a set of controlled subsystems, which are physically and digitally connected. The controlled subsystems have two operation modes: In the autonomous mode they achieve local tasks independently of each other, whereas in the synchronisation mode they perform given tasks synchronously by using communication. The paper proposes to model the networked discrete-event system by an Input/Ouput (I/O) automata network and gives a method for partial cooperation betw… Show more
“…By Corollary 1, E S (ε) = {0, 1, 2}. Since OUT obs ((α, 0), α) = OUT obs ((α, 1), α) = ε, by Equation (14), DOR( ẼS (ε), σ) = {(1, π 0 , ε, ε), (2, π 0 , ε, ε)}. By Definition 5, ẼS (α) = DUR(DOR( ẼS (ε), σ), S(α)).…”
mentioning
confidence: 90%
“…Such a network structure provides efficient ways for controlling DESs. However, the communication delays existing in the observation channel and the control channel pose significant challenges to the supervisory control of DESs [7][8][9][10][11][12][13][14].…”
In this paper, we investigate the modeling and control of networked discrete-event systems (DESs), where a supervisor is connected to the plant via an observation channel and the control commands issued by the supervisor are delivered to the actuator of the plant via a control channel. Communication delays exist in both the observation channel and the control channel. First, a novel modeling framework for the supervisory control of DESs subject to observation delays and control delays is presented. The framework explicitly models the interaction process between the plant and the supervisor over the communication channels. Compared with the previous work, a more accurate “dynamics” of the closed-loop system is specified. Under this framework, we further discuss how to estimate the states of the closed-loop system in the presence of observation delays and control delays. Based on the state estimation, we synthesize an optimal supervisor on the fly to maximize the controlled behaviors while preventing the system from leaving the desired behaviors under communication delays. We compare the proposed supervisor with the supervisor proposed in the literature and show that the proposed supervisor is more permissive. As an application, we show how the proposed approach can be applied to manage vehicles in a signal intersection. Finally, we show how to extend the proposed framework to model a system whose actuators and sensors are distributed at different sites.
“…By Corollary 1, E S (ε) = {0, 1, 2}. Since OUT obs ((α, 0), α) = OUT obs ((α, 1), α) = ε, by Equation (14), DOR( ẼS (ε), σ) = {(1, π 0 , ε, ε), (2, π 0 , ε, ε)}. By Definition 5, ẼS (α) = DUR(DOR( ẼS (ε), σ), S(α)).…”
mentioning
confidence: 90%
“…Such a network structure provides efficient ways for controlling DESs. However, the communication delays existing in the observation channel and the control channel pose significant challenges to the supervisory control of DESs [7][8][9][10][11][12][13][14].…”
In this paper, we investigate the modeling and control of networked discrete-event systems (DESs), where a supervisor is connected to the plant via an observation channel and the control commands issued by the supervisor are delivered to the actuator of the plant via a control channel. Communication delays exist in both the observation channel and the control channel. First, a novel modeling framework for the supervisory control of DESs subject to observation delays and control delays is presented. The framework explicitly models the interaction process between the plant and the supervisor over the communication channels. Compared with the previous work, a more accurate “dynamics” of the closed-loop system is specified. Under this framework, we further discuss how to estimate the states of the closed-loop system in the presence of observation delays and control delays. Based on the state estimation, we synthesize an optimal supervisor on the fly to maximize the controlled behaviors while preventing the system from leaving the desired behaviors under communication delays. We compare the proposed supervisor with the supervisor proposed in the literature and show that the proposed supervisor is more permissive. As an application, we show how the proposed approach can be applied to manage vehicles in a signal intersection. Finally, we show how to extend the proposed framework to model a system whose actuators and sensors are distributed at different sites.
“…No synthesis is done, however, the paper provides useful insights in distributing controllers and the required communication between controllers. [12] discusses synchronization of events in DES using networked controllers. Networked controllers are similar to distributed controllers in the sense that multiple local controllers communicate to apply control action to a plant.…”
In literature, extensive research has been done with respect to synthesis of supervisory controllers. Such synthesized supervisors can be distributed for implementation on multiple physical controllers. This paper discusses a method for distributing a synthesized supervisory controller. In this method, dependency structure matrices are used to distribute a system, the supervisor is then distributed accordingly, using existing localization theory. The existence of communication delays between supervisory controllers is unavoidable in a distributed application. The influence of these delays on the behavior of a supervisor is therefore studied using delay robustness theory. This paper introduces the use of mutex algorithms to make the distributed supervisor delay-robust. A case study is used to demonstrate the method and hardware in the loop testing is used to validate the resulting distributed supervisor.
“…A sincronização de SEDs foi abordada em Viana et al (2013); Pocci et al (2014); Zgorzelski & Lunze (2016); Alves & Pena (2018). Em nenhum destes trabalhos foi abordado o problema da implementação de um método para sistemas modelados por RPICs cuja sincronização seja feita agregando informações diretamente na estrutura das RPICs.…”
Section: Introductionunclassified
“…Em Pocci et al (2014); Alves & Pena (2018), o problema de sincronização foi tratado no sentido de lidar com recuperação de erros, utilizando palavras de sincronização. Em Zgorzelski & Lunze (2016), os autores propõem um método para sincronização de sistemas em rede utilizando autômatos I/O. Entretanto, não está claro como fazer a implementação de tal método.…”
In this work, a method is proposed to perform the implementation of the synchronization of discrete event systems with resource sharing, by using the common place technique. Two different approaches are presented for synchronization as well as two algorithms to implement the synchronization by using control interpreted petri net (CIPN). The implementation in a didactic mechatronic plant is carried out through programmable logic controllers (PLCs) connected to each other by means of an industrial communication network and programmed in Ladder logic. Resumo: Neste trabalho,é proposto um método para realizar a implementação da sincronização de sistemas a eventos discretos com compartilhamento de recursos, utilizando a técnica de lugares comuns. Dois tipos de abordagens para a sincronização são apresentados, assim como dois algoritmos para a implementação adaptados para rede de Petri interpretada para controle (RPIC). A implementação em uma planta mecatrônica didáticaé realizada através de controladores lógicos programáveis (CLPs) conectados em rede e programados em linguagem Ladder.
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