Identifying MIMO Hammerstein systems in the Context of Subspace Model Identification Methods

In this paper, we outline the extension of the MOESP (standing for Multivariable Output Error State sPace model identification and introduced in [1].) family of subspace model identification schemes to Hammerstein type of non-linear systems. One type of identification problem is considered. This type addresses the identification of both the linear dynamic part and the static nonlinearity, where only limited a priori information regarding the structure of the nonlinearity is available. Another (c) type of Hammerstein identification problem, considered in [2], assumes the (polynomial) structure of the static non-linearity to be given and the task here is to identify similarly the linear system dynamics and the unknown proportional constants in the parametrization of the static non-linearity. The improved robustness properties of the algorithms developed in this paper over existing correlation based schemes is illustrated in [2].