Transformational supervisor synthesis for evolving systems

Abstract

AbstractSupervisory controller synthesis is a means to compute correct-by-construction controllers for discrete event systems. As these systems and their requirements evolve over time, an updated supervisor needs to be computed each time an adaptation takes place. We consider the case that a supervisor has been synthesized for a given model, after which this model is (slightly) adapted. We investigate how we can make use of the previous synthesis result, in order to more efficiently compute the supervisor for the adapted model. We introduce model deltas as a means to describe the difference between pairs of models. Using the model deltas, a notion of atomic adaptations is introduced. For these atomic adaptations, algorithms are provided to compute the supervisor for the adapted model in a transformational manner from the previous synthesis result, rather than performing a completely new synthesis. These atomic adaptations can be iterated over, to transformationally compute a supervisor for model deltas that contain a number of atomic adaptations. To improve efficiency, it is shown how atomic adaptations can be grouped together based on their required computations and be processed at the same time. A running example is used to support the explanations on the functioning of the algorithms. The efficiency of the method is evaluated by means of both an academic and an industrial use case.