Evolving black box recursive modeling algorithm

In this paper an evolving recursive fuzzy cluster algorithm based on maximum likelihood criterion using the recursive instrumental variable parameter estimation for nonlinear system identification, is proposed. The performance of the proposed methodology is illustrated for black box modeling of a thermal plant from real-time acquisition data platform. The experimental results are evaluated from metrics used in the literature to show the efficiency of the proposed online evolving recursive fuzzy clustering algorithm.