A Model Based Approach to Simulation and Digital Twins
Presenters: Prof. Tony Clark, Aston University & Prof. Balbir Barn, Middlesex University & Souvik Barat, TCS Research
Tutorial - 108
We live in a hyperconnected world where systems must deal with unforeseen situations. Connectivity produces systems-of-systems whose scale makes it challenging to create a single design with a fixed centralised behaviour. The design, deployment and maintenance of such systems is increasingly a problem.
Systems must be engineered to accommodate uncertainty through dynamic adaptation. This can be achieved at inception by engineering for adaptation (endogenous) and by digital twins that measure differences between reality and objectives leading to corrective actions (exogeneous).
Such a view is enabled by organising systems or twins as a collection of communicating agents. Traditional systems represented in this way would implement each agent behaviour machine as a function whose range is a new state and associated output messages. The key enabler is to view an agent behaviour as a relation such that a single event can produce a set of possible actions so that systems have sets of local and global behaviours. At least one of the possible behaviours is consistent with the goal. The challenge is to select the right behaviour through simulation or incremental adaptation. Organising and interacting with systems in this way supports the discovery of effective behaviour.
This tutorial will introduce the participants to the approach outlined above. It will include a review of the need for Digital Twins in the context of complex system development, the approach is motivated by a conceptual model for twins as simulations that can achieve adaptation through learning. The tutorial will be supported using a technology platform that implements the concepts.