The University of British Columbia

This paper introduces a mechanism for testing multivariable models employed by model-based controllers. Although external excitation is not necessary, the data collection includes a stage where the controller is switched to open-loop operation (manual mode). The main idea is to measure a certain ``distance{''} between the closed-loop and the open-loop signals, and then trigger a flag if this ``distance{''} is larger than a threshold level. Moreover, a provision is made for accommodating model uncertainty. Since no hard bounds are assumed with respect to the noise amplitude, the model invalidation mechanism works in a probabilistic framework. (C) 2003 Elsevier Ltd. All rights reserved.