Black-Box Fuzzy Identification of a Nonlinear Hydrogen Fuel Cell Model - Bertone, Ana Maria Amarillo; Martins, Jefferson Beethoven; Yamanaka, Keiji (Trends in Computational and Applied Mathematics, 2018)
A fuzzy identification of the dynamical system model is developed upon a data generated by a software simulator of a hydrogen fuel cell. The data presents a black box model, just composed by inputs and outputs, carry no additional information, and showing a strong nonlinear behavior. The choice for a fuzzy identification is based on the data features, and the malleability of the mathematical fuzzy technique. This approach allows to accomplish the objectives of the research, among which, the validation of the method for it used in other industrial problems. The dynamic system identification process is performed using a fuzzy clustering through the Gustafson and Kessel algorithm, and a Takagi Sugeno fuzzy inference method. Validation tests are performed in terms of the 4-fold technique, confirming the lack of the data over-training. These results make the fuzzy approach looks as a promising tool for black-box identification of non linear dynamic systems.