Behavior Modelling of Embedded Real-Time Systems Operating in Uncertain Environments

Decisions made at uncertain environments by the embedded real-time systems (ERTS) have a long-term effect on the surroundings and users usually expect the system to behave intelligently. Implementation of expected behaviors and identifying nondeterministic behaviors of such systems operating in uncertain environments is a challenging issue for the embedded system designers. To cope with multiple tasks running in the same or several sub-systems and to manage the complexity of control as well as to improve the performance of the system, there is a need for stable modeling framework. This paper proposes a framework which can be applied to many ERTS applications, where the system behaviors can be predicted exactly during system in operation. Moreover, the architecture gives overall flexibility to apply all expected behaviors in different situations dynamically based on sensor responses.