Qualitative Reasoning and Cyber-Physical Systems: Abstraction, Modeling, and Optimized Simulation

Complex systems modeling and simulation are critical in many industrial and research fields and specifically to predict, prove, verify, and understand the behavior of cyber-physical systems. The diversity of variables in a system creates complexity [1] and a need for more efficient modeling and simulation methods. In the case of hybrid systems [2], the heterogeneity of the discrete and continuous parts makes these tasks more challenging by adding the necessity to manage different types of variables and transitions separately. Qualitative reasoning offers a paradigm to study the behavior of such systems with a high level of abstraction, trading precision and specificity against generality and formalism. This paradigm can be preferred to numerical analysis in specific situations, especially in the upstream study of a system, in its design phases. However, the different representations and the various contexts of such systems create an important obstacle to define a general methodology for applying qualitative reasoning and modeling to every case. In this article, we propose a method and a tool to unify different qualitative reasoning techniques on complex cyber-physical systems. We will also develop the possibilities offered by the obtained abstraction in various tasks such as formal proof, verification, property analysis, diagnosis, simulation driving, and system monitoring.