Non-linear dynamic system identification: a multi-model approach

We are concerned with models which are able to describe multiple-input mult iple-output (MIMO) non-linear dynamic systems. These models are represented in the form of rules and are known as Tagaki-Sugeno models. An identificat ion algorithm for these models based on input and output data is presented. Parameter estimation is based on the calculation of model sensitivity func tions with respect to their parameters. Some aspects of structure identific ation are also tackled, i.e. determination of local model orders and number of rules.