Embedded Model Predictive Control on a PLC Using a Primal-DualFirst-Order Method for a Subsea Separation Process

Abstract

The results of a PLC implementation of embedded Model Predictive Control (MPC) for an industrial problem are presented in this paper. The embedded MPC developed is based on the linear MPC module in SEPTIC (Statoil Estimation and Prediction Tool for Identification and Control), and it combines custom ANSI C code generation with problem size reduction methods, embedded real-time considerations, and a primal-dual first-order method that provides a fast and light QP solver obtained from the FiOrdOs code generator toolbox. Since the primal-dual first-order method proposed in this paper is new in the control community, an extensive comparison study with other state-of-the-art first-order methods is conducted to underline its potential. The embedded MPC was implemented on the ABB AC500 PLC, and its performance was tested using hardware-in-the-loop simulation of Statoil's newly patented subsea compact separation process. A warm-start variant of the proposed first-order method outperforms a tailored interior-point method by a factor of 4 while occupying 40% less memory.