An approach for fuzzy frequency response estimation of flexible robot arm from experimental data

An approach for fuzzy frequency response estimation of flexible robot arm from experimental data is proposed in this paper. A fuzzy c-Means clustering algorithm is used to organize the input and output experimental data of a flexible robot arm into groups based on similarities among the data. Starting from the fuzzy clustering a methodology for identification of the linear sub-models, in terms of transfer function, that represent the flexible robot arm in operation regions is developed and these linear sub-models are organized according to Takagi-Sugeno (TS) fuzzy representation. A fuzzy frequency estimation of the flexible robot arm is determined through the frequency response function. The main contribution of this paper is to demonstrate through the proposal of a Theorem, that fuzzy frequency response estimation is a boundary in the magnitude and phase Bode plots.