Dynamic Data Reconciliation to Decrease the Effect of Measurement Noise on Controller Performance Assessment

Controller performance assessment (CPA) is capable to evaluate the controller performance and has been widely used in industrial processes. In the existing research studies, CPA usually assumes that the feedback signals are the actual process outputs without considering the measurement noise. Minimum variance (MV)-based CPA is the most common method for controller performance evaluation. In this paper, the effect of measurement noise is considered in the feedback signals of the MV-based CPA. The dynamic data reconciliation (DDR) is incorporated in the MV-based CPA (DDR-MV-CPA) to decrease the effect of measurement noise on CPA. The effectiveness of the proposed DDR-MV-CPA method is demonstrated via theoretical derivation, simulations, and experimental comparisons. (c) 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.