Performance Assessment and Model Validation of Two Industrial MPC Controllers

This paper presents two case studies on the performance evaluation and model validation of two industrial multivariate model predictive control (MPC) based controllers at Suncor Energy Inc., Fort McMurray, Canada: (1) a 7 controlled variable (CV), 3 manipulated variables (MV) kerosene hydrotreating unit (KHU) with three measured disturbance variables that are used for feedforward control; and (2) an 8 CV, 4 MV naphtha hydrotreating unit (NHU) with 5 measured disturbances. The NHU and KHU controllers are implemented on the product stripping distillation towers. The first case study focuses on potential limits to control performance due to constraints and limits set at the time of controller commissioning. The root causes of sub-optimal performance of KHU are successfully isolated. Data from the NHU unit with MPC on and with MPC off are analyzed to obtain and compare several different measures of multivariate controller performance. Model quality assessment for the two MPCs are performed. A new model index is proposed to have a measure of simulation ability and prediction ability of a model. Open-loop identification of KHU and closed-loop identification of NHU are conducted using the asymptotic method (ASYM).