Closed-loop model validation based on the two-model divergence method

This paper is concerned with model validation and detection of parameter changes under closed-loop conditions in the discrete time domain. A control relevant validation algorithm is developed based on the two-model divergence method. The algorithm is only sensitive to the plant changes that affect closed-loop performance. Also, an important advantage of the algorithm is that it is only sensitive to the changes in plant dynamics, irrespective of changes in disturbance dynamics. For the situation where the changes in plant dynamics are not a concern, then the algorithm can also be applied to detect process faults, e.g. sensor decalibration and valve stiction. The developed algorithm is evaluated by simulations as well as experimental application on a pilot scale process.