Model selection for servo control systems

Physically motivated models of electromechanical motion systems are required in several applications related to control design, model-based fault detection and simply interpretation. Often, however, the high effort of modelling prohibits these model-based methods in industrial applications. Therefore, all approaches of automatic modelling / model selection are naturally appealing. An intuitive approach is to identify the parameters of several model candidates and to select the one with the best fit on unseen data. A shortcoming of this approach is that the chosen model may be one with high complexity in which some of the physically interpretable parameters are not practically identifiable and uncertain. Also, ambiguities in selecting the model structure would not be disguised resulting in false confidence in a chosen model. Designing a reasonable set of candidate models requires that distinguishability of models can be checked prior to the identification procedure.