Subspace state space system identification for industrial processes

We give a general overview of the state-of-the-art in subspace system identi®cation methods. We have restricted ourselves to the most important ideas and developments since the methods appeared in the late eighties. First, the basics of linear subspace identi- ®cation are summarized. Di€erent algorithms one ®nds in literature (such as N4SID, IV-4SID, MOESP, CVA) are discussed and put into a unifying framework. Further, a comparison between subspace identi®cation and prediction error methods is made on the basis of computational complexity and precision of the methods by applying them on 10 industrial data sets.