Authors:
Manuela L. Bujorianu
and
Marius C. Bujorianu
Affiliation:
University of Manchester, United Kingdom
Keyword(s):
Cyber-physical systems, Adaptive bisimulation, Co-evolution, Stochastic model checking, Qualitative model reduction, Nanoscience.
Related
Ontology
Subjects/Areas/Topics:
Hybrid Dynamical Systems
;
Informatics in Control, Automation and Robotics
;
Modeling, Simulation and Architectures
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
The problem of abstracting computational relevant properties from sophisticated mathematical models of physical environments has become crucial for cyber-physical systems. We approach this problem using Hilbertean formal methods, a semantic framework that offers intermediate levels of abstractions between the physical world described in terms of differential equations and the formal methods associated with theories of computation. Although, Hilbertean formal methods consider both deterministic and stochastic physical environments, in this paper, we focus on the stochastic case. The abstraction method can be used for verification, but also to improve the controller design and to investigate complex interactions between computation and physics. We define also a computational equivalence relation called adaptive model reduction, because it considers the co-evolution between a computation device environment and its physical environment during abstraction.