Recursive fuzzy instrumental variable based evolving neuro-fuzzy identification for non-stationary dynamic system in a noisy environment

In this paper an online identification algorithm for instrumental variable based evolving neuro fuzzy modeling applied to dynamic systems in noisy environment, is proposed. The adopted methodology is based an online neuro-fuzzy inference system with Takagi-Sugeno evolving structure, which employs an adaptive distance norm based on the maximum likelihood criterion with instrumental variable recursive parameter estimation. The application and performance analysis of the proposed algorithm is based on black box modeling of a 2DOF Helicopter with errors in the variables.