Visible to the public Building Power Consumption Models from Executable Timed I/O Automata Specifications

TitleBuilding Power Consumption Models from Executable Timed I/O Automata Specifications
Publication TypeConference Paper
Year of Publication2016
AuthorsBarbot, Benoît, Kwiatkowska, Marta, Mereacre, Alexandru, Paoletti, Nicola
Conference NameProceedings of the 19th International Conference on Hybrid Systems: Computation and Control
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-3955-1
Keywordscomposability, CPS modeling, data-driven energy consumption models, Embedded systems, energy optimisation, hardware-in-the-loop simulation, Metrics, Petri nets, pubcrawl, Resiliency, satisfiability modulo theories, simulation, Synthesis, timed i/o automata, verification
Abstract

We develop a novel model-based hardware-in-the-loop (HIL) framework for optimising energy consumption of embedded software controllers. Controller and plant models are specified as networks of parameterised timed input/output automata and translated into executable code. The controller is encoded into the target embedded hardware, which is connected to a power monitor and interacts with the simulation of the plant model. The framework then generates a power consumption model that maps controller transitions to distributions over power measurements, and is used to optimise the timing parameters of the controller, without compromising a given safety requirement. The novelty of our approach is that we measure the real power consumption of the controller and use thus obtained data for energy optimisation. We employ timed Petri nets as an intermediate representation of the executable specification, which facilitates efficient code generation and fast simulations. Our framework uniquely combines the advantages of rigorous specifications with accurate power measurements and methods for online model estimation, thus enabling automated design of correct and energy-efficient controllers.

URLhttp://doi.acm.org/10.1145/2883817.2883844
DOI10.1145/2883817.2883844
Citation Keybarbot_building_2016