An algorithm for fuzzy identification of nonlinear discrete-time systems

Abstract

An approach to fuzzy identification of discrete-time nonlinear dynamical systems with a suitable formulation, based on the Takagi-Sugeno (TS) model is proposed. To form the fuzzy model from samples of a nonlinear dynamical system where the consequent parameters are modified by an adaptive weighted instrumental variable (WIV) algorithm based on the numerically robust orthogonal Householder transformation, offline and online schemes are developed. To show the consistency, high speed of convergence, tracking of the output that vary with time and the high accuracy of the output estimate, important in adaptive control design applications, simulations are performed.