Synthesis of communicating controllers for distributed systems

Abstract

Abstract-We consider the control of distributed systems composed of subsystems communicating asynchronously; the aim is to build local controllers that restrict the behavior of a distributed system in order to satisfy a global state avoidance property. We model our distributed systems as communicating finite state machines with reliable unbounded FIFO queues between subsystems. Local controllers can only observe their proper local subsystems and do not observe the queues. To refine their control policy, they can use the FIFO queues to communicate by piggybacking extra information to the messages sent by the subsystems. We define synthesis algorithms allowing to compute the local controllers. We explain how we can ensure the termination of this control algorithm by using abstract interpretation techniques, to overapproximate queue contents by regular languages. An implementation of our algorithms provides an empirical evaluation of our method. I. INTRODUCTIONIn the framework of control of distributed systems, two classes of systems are generally considered, depending on whether the communications between subsystems are synchronous or not. When the synchrony hypothesis [3] can be made, the decentralized control problem and the modular control problem address the design of coordinated controllers that jointly ensure the desired properties for this kind of systems [26], [22], [21], [9], [13]. When considering asynchronous distributed systems, one have to take into account some communication delays between the components of the system, which renders the distributed control problem much harder even undecidable [24].We are here interested in the second problem i.e., the distributed control problem. Our aim is to solve this problem when the system to be controlled is composed of n subsystems that asynchronously communicate through reliable unbounded FIFO channels (or queues). These subsystems are modeled by communicating finite state machines [5] (CFSM for short) that explicitly express the work and communications of a distributed system. This model appears to be essential for concurrent systems in which components cooperate via asynchronous message passing through unbounded buffers (they are e.g. widely used to model communication protocols). We thus assume that the distributed system is already built and the architecture of communication between the different subsystems is fixed. Following the architecture described in Figure 1, we assume that each subsystem is

Distributed supervisory control of discrete-event systems with communication delay

“…In this case, we say that SUP is 'bounded' delay-robust with respect to r. 8 We illustrate the foregoing results by an example adapted from [21]. 7 For the case described in Section III-B of transmitting multiple events by separate channels, we use the same method to check if each event r is blocked. Specifically, we check if P −1 r L(CH(i, r, j)) is NSUP-controllable with respect to r, where NSUP denotes the behavior of the system excluding CH(i, r, j).…”

“…The communication problem in distributed control of multi-agent DES has been discussed by several researchers. Kalyon et al [7] propose a framework for the control of distributed systems modeled as communicating finite state machines with reliable unbounded FIFO channels. They formulate a distributed state avoidance control problem, and show that the existence of a solution for the problem is undecidable.…”

Symbolic Supervisory Control of Distributed Systems With Communications

“…This paper is an extended version of two conference papers [18] and [17]. It provides the full process allowing to derive controllers from a state-based specification and a plant by means of state-based estimates and abstract interpretation techniques, whereas [17] was only presenting the state-based algorithms and [18] the control point of view with an overview of the state-based estimates computation point of view. The proofs absent from this paper are available in [16].…”

METHODS OF COMPLEX OBJECT’S TRANSFER FUNCTION CALCULATION FOR DISTRIBUTED CONTROL SYSTEM

“…In this case the distributed object (system) can be structurally presented as the infinite set of the independent conditionally concentrated contours. Transfer function of the each of their conditionally concentrated contour can be presented in the form of the analytical entire functions' relation (Kalyon, 2010).…”