Partners: ABB, SASOL, Boliden, TUDelft, AWTH, TU/e, KTH
It is widely recognized that the life-time performance of current model-based operation support systems, like Model Predictive Control (MPC), Real-Time Optimization (RTO) and soft-sensors for large-scale complex dynamic processes is rather limited, particularly due to the fact that the underlying dynamic models need to be adapted/calibrated regularly, requiring dedicated measurement campaigns executed by highly specialized engineers. In this project, we aimed to develop technology in order to bring the current model-based operation support technology to a higher level of autonomy. Such a technology requires developments in experiment design, performance monitoring and diagnosis, closed loop identification, autotuning so that it can optimize plant performance under varying operational conditions and adapting to changing circumstances.
Figure 1: Autoprofit Decision Tree