Iterative Method in the Identification of Block-Oriented Systems Based on Biconvex Optimization

In this paper, we investigate the identification of the class of block-oriented nonlinear systems presented by Li et al. [2011] by using an iterative method. Firstly a common model is proposed to represent such block-oriented systems. Then identifying the common model is formulated as a biconvex optimization problem. Based on this, a normalized alterative convex search (NACS) algorithm is proposed under a given arbitrary nonzero initial condition. It is shown that we only need to find the unique partial optimum point of a biconvex cost function in the formulated optimization problem in order to obtain its global minimum point. Thus, the convergence property of the proposed algorithm is established under arbitrary nonzero initial conditions. The approach presented in this paper provides a unified framework for the identification of block-oriented systems.