Abstract

This paper presents an online identification algorithm based on instrumental variable evolving neuro fuzzy model applied to dynamic systems in noisy enviroment. 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 performance and application of the proposed algorithm is based on the black box modeling of a 2DOF Helicopter with errors in variables.

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