4,252 research outputs found

    Compositional synthesis of discrete event systems via synthesis equivalence

    Get PDF
    A two-pass algorithm for compositional synthesis of modular supervisors for largescale systems of composed finite-state automata is proposed. The first pass provides an efficient method to determine whether a supervisory control problem has a solution, without explicitly constructing the synchronous composition of all components. If a solution exists, the second pass yields an over-approximation of the least restrictive solution which, if nonblocking, is a modular representation of the least restrictive supervisor. Using a new type of equivalence of nondeterministic processes, called synthesis equivalence, a wide range of abstractions can be employed to mitigate state-space explosion throughout the algorithm

    Compositional abstraction and safety synthesis using overlapping symbolic models

    Full text link
    In this paper, we develop a compositional approach to abstraction and safety synthesis for a general class of discrete time nonlinear systems. Our approach makes it possible to define a symbolic abstraction by composing a set of symbolic subsystems that are overlapping in the sense that they can share some common state variables. We develop compositional safety synthesis techniques using such overlapping symbolic subsystems. Comparisons, in terms of conservativeness and of computational complexity, between abstractions and controllers obtained from different system decompositions are provided. Numerical experiments show that the proposed approach for symbolic control synthesis enables a significant complexity reduction with respect to the centralized approach, while reducing the conservatism with respect to compositional approaches using non-overlapping subsystems

    Transition removal for compositional supervisor synthesis

    Get PDF
    This paper investigates under which conditions transitions can be removed from an automaton while preserving important synthesis properties. The work is part of a framework for compositional synthesis of least restrictive controllable and nonblocking supervisors for modular discrete event systems. The method for transition removal complements previous results, which are largely focused on state merging. Issues concerning transition removal in synthesis are discussed, and redirection maps are introduced to enable a supervisor to process an event, even though the corresponding transition is no longer present in the model. Based on the results, different techniques are proposed to remove controllable and uncontrollable transitions, and an example shows the potential of the method for practical problems

    Abstraction and Learning for Infinite-State Compositional Verification

    Full text link
    Despite many advances that enable the application of model checking techniques to the verification of large systems, the state-explosion problem remains the main challenge for scalability. Compositional verification addresses this challenge by decomposing the verification of a large system into the verification of its components. Recent techniques use learning-based approaches to automate compositional verification based on the assume-guarantee style reasoning. However, these techniques are only applicable to finite-state systems. In this work, we propose a new framework that interleaves abstraction and learning to perform automated compositional verification of infinite-state systems. We also discuss the role of learning and abstraction in the related context of interface generation for infinite-state components.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455

    On the use of observation equivalence in synthesis abstraction

    Get PDF
    In a previous paper we introduced the notion of synthesis abstraction, which allows efficient compositional synthesis of maximally permissive supervisors for large-scale systems of composed finite-state automata. In the current paper, observation equivalence is studied in relation to synthesis abstraction. It is shown that general observation equivalence is not useful for synthesis abstraction. Instead, we introduce additional conditions strengthening observation equivalence, so that it can be used with the compositional synthesis method. The paper concludes with an example showing the suitability of these relations to achieve substantial state reduction while computing a modular supervisor

    Sparsity-Sensitive Finite Abstraction

    Full text link
    Abstraction of a continuous-space model into a finite state and input dynamical model is a key step in formal controller synthesis tools. To date, these software tools have been limited to systems of modest size (typically ≤\leq 6 dimensions) because the abstraction procedure suffers from an exponential runtime with respect to the sum of state and input dimensions. We present a simple modification to the abstraction algorithm that dramatically reduces the computation time for systems exhibiting a sparse interconnection structure. This modified procedure recovers the same abstraction as the one computed by a brute force algorithm that disregards the sparsity. Examples highlight speed-ups from existing benchmarks in the literature, synthesis of a safety supervisory controller for a 12-dimensional and abstraction of a 51-dimensional vehicular traffic network
    • …
    corecore