Exploring the Cyber‐Physical Design Space

Abstract

A major challenge in the model‐based engineering of Cyber‐Physical Systems (CPSs) is that of providing methods and tools that support decision‐making in design. In the CPS design space, system models may be composed of diverse notations and tools, and the range of alternatives to be evaluated is immense. In spite of this, the benefits of trade‐off analysis at an early design stage are significant, making the automation of Design Space Exploration (DSE) an appealing prospect. In bringing DSE to industry scale, there is a clear need for both guidance to engineers in designing DSE, and a theory of cost‐effective DSE algorithms. To address this, we propose and demonstrate a SysML profile that encourages the explicit description of DSE over multi‐disciplinary co‐models, and demonstrate the ability to tune a genetic DSE algorithm across a range of design spaces.

Features of Integrated Model-Based Co-modelling and Co-simulation Technology

“…For example, varying n parameters with m alternative values produces a design space of m n alternatives. We have therefore implemented genetic approaches [15].…”

“…CPS engineering necessarily involves a wide range of modelling and programming paradigms [13], including concurrency, real-time, mobility, continuous variables, differential equations, object orientation, and diagrammatic languages. Practical CPS engineering uses a variety of domain-specific and general-purpose languages, such as Simulink, Modelica, SysML, Java, and C, and engineering trustworthy CPS requires that semantic models for these languages are integrated in a consistent way, which then enables reasoning about an entire CPS 15 .…”

A multi-modelling based approach to assessing the security of smart buildings

“…If there is only a single performance measure than results may simply be placed in an list, ordered by that measure, to find the best, however, if there are multiple measures then a different means for comparison must be used. In the latter case, INTO-CPS makes uses the Pareto method to present the user with a nondominated set of best designs [9].…”

A feasibility assessment of multi-modelling approaches for rail decarbonisation systems simulation

“…7,8 Multi-modelling offers a solution to address this simulation challenge. 9,10 Multi-modelling is the application of two, complimentary technologies -Functional Mock-up Interface (FMI) 11,12 and co-simulation. 13 FMI is a standard format, widely adopted in sectors such as automotive and aerospace [e.g.…”