Robust Structured Nonlinear System Identification

In this paper we offer an extension to the structured system identification problem. In the presence of model uncertainty, the standard identification procedure may lead to inherently biased estimates. Here, we propose a systematic approach towards incorporating model uncertainty into the identification algorithm. The uncertainty is introduced as a set membership constraint and the computation is reduced to a convex minimization problem