Dual control approach for zone model predictive control

Over the last few years, model based predictive controller (MPC) has gained popularity in many industrial fields one of which is the building climate control. In order to work properly, the MPC needs a model of a controlled system which describes the reality as accurate as possible. In practice, the model used by the MPC often becomes inapplicable due to the change of either the operating point or other conditions which leads to control performance degradation. In such a situation, it is inevitable to re-identify the model. However, in a majority of cases, the data available for the re-identification are from the closed-loop and they do not contain enough information for the successful re-identification of the model. In this paper, a dual control algorithm based on the maximization of the smallest eigenvalue of the information matrix increase ensuring both the appropriately informative data and satisfaction of the control performance is presented. As the area of the interest is the building climate control, we offer the dual control algorithm for a specific class of the zone MPC which is widely used in this field.