Direct continuous-time approaches to system identification. Overview and benefits for practical applications
Résumé
This talk discusses the importance and relevance of direct continuous-time system identification and how this relates to the solution for model identification problems in practical applications. It first gives a tutorial introduction to the main aspects of the most successful existing approaches for directly identifying continuous-time models of dynamical systems from sampled input-output data, including a review of associated software that has been developed to implement this methodology. Compared with traditional discrete-time model identification methods, the direct continuous-time approaches have some notable advantages that make them more useful in many practical applications. For instance, continuous-time models are more intuitive to control scientists and engineers in their every-day practice and the related estimation methods are particularly well suited to handle rapidly or irregularly sampled data situations. The second part of the talk discusses and illustrates these advantages via simulated and real data examples.