Dynamic models are widely used to assess stability through simulations. The accuracy of the dynamic models affects the validity of the stability assessment. The accuracy depends on the assumed model structure and the values of its parameters. Model identification deals with setting the appropriate values of the parameters, but it is essential that these values are valid under different conditions. This project tackles the problem of tuning the model parameters in a robust way in the sense that the response of the dynamic model is representative for different conditions. 1) Literature review 2) Development of a robust tuning approach 3) Implementation in AMOR 4) Sensitivity studies
