Neuro-Fuzzy Based Approach for Identification of a Phantom Robot

Robots control is affected by accuracy of their model. In this paper, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model is used for Single Input and Single Output (SISO) and Multiple Input Single output (MISO) identification of the non-linear model of a Phantom robot from SensAble Technologies, Inc. In addition, we provide a comprehensive comparison by implementing five different intelligent identification methods, which are used frequently in the literature. The experimental results show the effectiveness of the proposed method in comparison with other methods in term of Phantom robot modelling.