Application of cyber physical systems to chemical plants: Economic MPC in batch processes

Abstract

Cyber physical systems (CPS), which realize the real-time perception, dynamic control and information services of large-scale engineering systems through the organic integration and deep collaboration of 3C (Computer, Communication, Control) technologies, are a highly anticipated technology to solve the issues of modern plants innovatively. The significance of CPS is to connect the physical device to the internet, allowing the physical device to have five functions of computing, communication, precise control, remote coordination and autonomy. Among these CPS technologies used in industrial processes, economic model predictive control (MPC), which is a control scheme for industrial process with optimization economic as an indicator, is considered a forerunner approach towards plant process automation. However, most published papers on economic MPC applications have focused on continuous processes and only a few researchers have turned their attention to batch processes. This research studies economic MPC strategies for batch processes to evaluate its applicability. Most batch processes exhibit highly nonlinear and time-varying behavior, which makes it difficult to control them. We applied economic MPC and PID control scheme to a batch process, observing that economic MPC scheme showed better control performance in speed, disturbance suppression and efficiency. Moreover, from a simulation result of max production rate control with economic MPC, it was revealed that process constraints affect production rate considerably, which indicates that economic MPC can be used not only for process control but also for process design. Off-line study with economic MPC can assess the effect of plant specification on plant efficiency quantitively. This paper revealed that economic MPC can improve both design and control of batch processes.