MODELING REAL - WORLD CONTROL SYSTEMS : BEYOND HYBRID SYSTEMS Stephen

Hybrid system modeling refers to the construction of system models combining both continuous and discrete dynamics. These models can greatly reduce the complexity of a physical system model by abstracting some of the continuous dynamics of the system into discrete dynamics. Hybrid system models are also useful for describing the interaction between physical processes and computational processes, such as in a digital feedback control system. Unfortunately, hybrid system models poorly capture common software architecture design patterns, such as threads, mobile code, safety, and hardware interfaces. Dealing effectively with these practical software issues is crucial when designing real-world systems. This paper presents a model of a complex control system that combines continuous-state physical system models with rich discrete-state software models in a disciplined fashion. We show how expressive modeling using multiple semantics can be used to address the design difficulties in such a system.