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A new approach to tracking control of networked discrete-event systems
Abstract
This paper presents a method for the tracking control of discrete-event systems that utilise digital communication only if the communication among the subsystems is necessary for solving the current task. The controlled subsystems are modelled by Input/Output (I/O)-automata and their local control aim is to reach given final states autonomously. The necessity of communication arises when there are synchronous state transitions on the state sequence into the final state, which may only be executed simultaneously by a set of subsystems. A new network unit is introduced, which extends each controlled subsystem in order to satisfy these cooperative tasks. It detects, initiates and ensures the simultaneous execution of the synchronous state transitions by means of the digital communication network. It is proved that the networked system is guaranteed to satisfy the local tasks in the networked discrete-event system, while executing the synchronous state transitions only synchronously. A cooperative car assembling process is used to demonstrate the proposed method.
... 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.
A method for the cooperative control of networked discrete-event systems is evaluated experimentally on a handling system. Networked discrete-event systems consist of controlled subsystems, which have to solve local and cooperative tasks. Local tasks are specified by target states of each individual subsystem, whereas cooperative tasks are modelled by synchronous state transitions for neighbouring subsystems. Network units connect the controlled subsystems via a digital network and apply situation dependent communication, if a cooperation is necessary. The experiments show that the proposed method is suitable to provide a flexibly structured handling system and that it is feasible with regard to the computational complexity.
We investigate state estimation and safe controller synthesis for networked discrete-event systems (DES), where supervisors send control decisions to plants via communication channels subject to communication delays. Previous works on state estimation of networked DES are based on the open-loop system without utilizing the knowledge of the control policy. In this paper, we propose a new approach for online estimation and control of networked DES with control delays. We first propose a new state estimation algorithm for the closed-loop system utilizing the information of control decision history. The proposed state estimation algorithm can be implemented recursively upon the occurrence of each new observable event. Then we investigate how to predict the effect of control delays in order to calculate a control decision online at each instant. We show that the proposed online supervisor can be updated effectively and the resulting closed-loop behavior is safe. Furthermore, we compare the proposed online supervisor with the predictive supervisor proposed in the literature and show that our proposed online supervisor is more permissive than predictive supervisor in
Networked discrete-event systems like smart manufacturing systems consist of subsystems, which are physically coupled and digitally connected by a communication network. The subsystems are able to solve their local tasks autonomously and to cooperate with another subsystem if necessary. In the second situation, the network units of both subsystems initiate the cooperation via the communication network. The flexibility of the subsystems to solve autonomous and cooperative tasks demonstrates an important property that is required for manufacturing systems in Industry 4.0. The paper concerns the situation that a fault occurs within a subsystem, which has to be detected and the controller has to be adapted. To this aim, the subsystems are extended by a diagnostic unit and a reconfiguration unit. The diagnostic unit detects and identifies the fault, whereas the reconfiguration unit applies a locally reconfigured controller. It is shown that if the fault has the property to be networked reconfigurable, the fault is locally reconfigurable without affecting the overall system.
This paper considers networked discrete-event systems. Local state-feedback controllers enable each subsystem to reach local target states. Due to the physical restrictions between the subsystems, the local target states might not be reachable autonomously, but cooperatively with the help of other subsystems. Therefore, each subsystem is extended by a network unit, which detects and resolves possible physical restrictions. If cooperation is necessary, the network units temporarily modify their local target states while applying situation-dependent communication. The proposed method is applied to the flexible manufacturing system HANS and its applicability to real-life systems is demonstrated by experimental results.
Modern engineering systems and cyber‐physical systems often consist of many distributed and networked physical plants, control units, and other devices with wired or wireless communication networks to exchange information between controllers and plants. These systems are called networked systems. In this article, we review supervisory control of networked discrete‐event systems. We first discuss how to model networked discrete‐event systems and how to obtain state estimates using a networked observer. We then introduce and solve the following supervisory control problems of networked discrete‐event systems: (i) (nondeterministic) supervisory control problem, (ii) deterministic supervisory control problem, (iii) nonblocking supervisory control problem, (iv) robust supervisory control problem, (v) robust deterministic supervisory control problem, (vi) deterministic decentralized supervisory control problem, and (vii) nonblocking decentralized supervisory control problem. We present and prove necessary and sufficient conditions for solving the above problems. Finally, we list the open problems in supervisory control of networked discrete‐event systems.
In this paper, we investigate the robust control problem of discrete event systems in a networked environment. In other words, we use a supervisor to control several possible plants (discrete event systems) to achieve given specifications when there are communication delays and losses in communication networks linking the supervisor and the plants. We translate the robust networked control problem into a conventional networked control problem by constructing an augmented automaton for all possible plants and an augmented specification automaton for the corresponding specification automata. We then solve the robust networked control problem. We consider two cases. The first case is when all the specifications are the same. For this case, we derive a necessary and sufficient condition for the existence of a robust networked supervisor. The second case is when the specifications are different, which is more general compared with the first case. In the second case, we can only obtain a sufficient condition for the existence of a networked supervisor. The results are illustrated by an example of customized products filling line.