A self-learning Digital Twin for Process Control of fast processes under Uncertainty KU Leuven
With the recent developments of sensor technologies appear new opportunities for conducting increasingly efficient and close control of industrial processes. This paper proposes a new scheme for near real-time process control of extremely fast complex processes using the framework of digital twins and an adaptively calibrating grey-box model. It focuses specifically on processes for which first-principle based numerical simulation is ...