An algorithm for weak synthesis observation equivalence for compositional supervisor synthesis

This paper proposes an algorithm to simplify automata in such a way that compositional synthesis results are preserved in every possible context. It relaxes some requirements of synthesis observation equivalence from previous work, so that better abstractions can be obtained. The paper describes the algorithm, adapted from known bisimulation equivalence algorithms, for the improved abstraction method. The algorithm has been implemented in the DES software tool Supremica and has been used to compute modular supervisors for several large benchmark examples. It successfully computes modular supervisors for systems with more than 1012 reachable states

Synthesis equivalence of triples

This working paper describes a framework for compositional supervisor synthesis, which is applicable to all discrete event systems modelled as a set of deterministic automata. Compositional synthesis exploits the modular structure of the input model, and therefore works best for models consisting of a large number of small automata. State-space explosion is mitigated by the use of abstraction to simplify individual components, and the property of synthesis equivalence guarantees that the final synthesis result is the same as it would have been for the non-abstracted model. The working paper describes synthesis equivalent abstractions and shows their use in an algorithm to compute supervisors efficiently. The algorithm has been implemented in the DES software tool Supremica and successfully computes modular supervisors, even for systems with more than 1014 reachable states, in less than 30 seconds

Synthesis observation equivalence and weak synthesis observation equivalence

This working paper proposes an algorithm to simplify automata in such a way that compositional synthesis results are preserved in every possible context. It relaxes some requirements of synthesis observation equivalence from previous work, so that better abstractions can be obtained. The paper describes the algorithm, adapted from known bisimulation equivalence algorithms, for the improved abstraction method. The algorithm has been implemented in the DES software tool Supremica and has been used to compute modular supervisors for several large benchmark examples. It successfully computes modular supervisors for systems with more than 10¹² reachable states

On the use of observation equivalence in synthesis abstraction

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

Three variations of observation equivalence preserving synthesis abstraction

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

Transition removal for compositional supervisor synthesis

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

SYNTHESIS EQUIVALENCE OF TRIPLES

This working paper describes a framework for compositional supervisor synthesis, which is applicable to all discrete event systems modelled as a set of deterministic automata. Compositional synthesis exploits the modular structure of the input model, and therefore works best for models consisting of a large number of small automata. The state-space explosion is mitigated by the use of abstraction to simplify individual components, and the property of synthesis equivalence guarantees that the final synthesis result is the same as it would have been for the non-abstracted model. The working paper describes synthesis equivalent abstractions and shows their use in an algorithm to efficiently compute supervisors. The algorithm has been implemented in the DES software tool Supremica and successfully computes nonblocking modular supervisors, even for systems with more than 1014 reachable states, in less than 30 seconds

Certainly Unsupervisable States

This paper proposes an abstraction method for compositional synthesis. Synthesis is a method to automatically compute a control program or supervisor that restricts the behaviour of a given system to ensure safety and liveness. Compositional synthesis uses repeated abstraction and simplification to combat the state-space explosion problem for large systems. The abstraction method proposed in this paper finds and removes the so-called certainly unsupervisable states. By removing these states at an early stage, the final state space can be reduced substantially. The paper describes an algorithm with cubic time complexity to compute the largest possible set of removable states. A practical example demonstrates the feasibility of the method to solve real-world problems

Five abstraction rules to remove transitions while preserving compositional synthesis results

This working 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