Assessing the Performance of Model Predictive Controllers

Abstract

Abstract Performance assessment of model predictive controllers is a problem of significant industrial relevance. Model predictive controllers belong to a class of linear time‐varying controllers, which compute the future control actions by minimizing a constrained, time‐varying objective function. In this work we propose a performance statistic that takes into account the time‐varying and constrained nature of model predictive control. The proposed measure compares the achieved objective function with its design value, online. Analytical expressions are derived to calculate the expected value of the design objective function under closed loop conditions. Simulation and industrial case studies are used to illustrate the applicability of the proposed metric.