Treffer: Machine Learning in Model Predictive Control, Operational Safety and Cybersecurity

Big data is considered to play an important role in the fourth industrial revolution, which requires engineers and computers to fully utilize data to make smart decisions and improve the performance of industrial processes and of their control and safety systems. Traditionally, industrial process control systems rely on a (usually linear) data-driven model with parameters that are identified from industrial/simulation data, and in certain cases, for example, in profit-critical control loops, on first-principles models (with data-determined model parameters) that describe the underlying physico-chemical phenomena. However, modeling large-scale, complex nonlinear processes continues to be a major challenge in process systems engineering. Modeling is particularly important now and into the future, as process models are key elements of advanced model-based control systems, e.g., model predictive control (MPC) and economic MPC (EMPC).Due to the wide variety of applications, machine learning models have great potential, yet, the development of rigorous and systematic methods for incorporating machine learning techniques in nonlinear process control and operational safety is in its infancy. Traditionally, operational safety of chemical processes has been addressed through process design considerations and through a hierarchical, independent design of control and safety systems. However, the consistent accidents throughout chemical process plant history (including several high profile disasters in the last decade) have motivated researchers to design control systems that explicitly account for process operational safety considerations. In particular, a new design of control systems such as model predictive controllers (MPC) that incorporate safety considerations and can be coordinated with safety systems has the potential to significantly improve process operational safety and avoid unnecessary triggering of alarms systems, where machine learning techniques can be utilized