Black-box modeling of nonlinear system using evolutionary neural NARX model

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Abstract

Nonlinear systems with uncertainty and disturbance are very difficult to model using mathematic approach. Therefore, a black-box modeling approach without any prior knowledge is necessary. There are some modeling approaches have been used to develop a black box model such as fuzzy logic, neural network, and evolution algorithms. In this paper, an evolutionary neural network by combining a neural network and a modified differential evolution algorithm is applied to model a nonlinear system. The feasibility and effectiveness of the proposed modeling are tested on a piezoelectric actuator SISO system and an experimental quadruple tank MIMO system.

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Son, N. N., Khanh, N. D., & Chinh, T. M. (2019). Black-box modeling of nonlinear system using evolutionary neural NARX model. International Journal of Electrical and Computer Engineering, 9(3), 1861–1870. https://doi.org/10.11591/ijece.v9i3.pp1861-1870

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