Recursive Subspace Identification for Closed-loop Systems

Abstract

The problem of recursive subspace identification of state-space models in closed-loop is considered in this paper. A new recursive algorithm based on stochastic approximation-principal component analysis (SA-PCA) is proposed to estimate a basis of the extended observability matrix in the noise-free case. The algorithm is evaluated by a simulation study.