Control and Decision Communication Across Heterogeneous Model Types

Abstract

Different classes of dynamical models are commonly used to understand and build mixed computational and physical systems. Cyber-Physical Systems are commonly simulated using hybrid continuous and discrete time modeling methods. As irregular control and decision continue to play more prominent roles due to increasing system complexity, it is useful to make better use of discrete-event modeling. Employing these inherently different classes of modeling theories should lead to higher support for restraining model development and simulation execution complexity. This is because three types of communication can be distinctly formalized for biological, physical, and computational systems. This leads to a more robust use of the simulation protocols and algorithms distinctly suitable for executing continuous, discrete-time, and discrete-event models. The DEVS-Suite and OpenModelica simulators, grounded in the DEVS and Modelica languages and their respective execution engines, are used together with FMI. The DEVS-Suite simulator inherently lends itself to modeling continuous-time event-oriented as well as discrete-time systems. Illustrative examples using Composable Cellular Automata, DEVS, ODE, and PDE are used to illustrate the benefit of modeling varied model structures and behaviors inherent in hybrid systems-of-systems.