Identification of Rigid-Body Dynamics of Robotic Manipulators Using Type-2 Fuzzy Logic Filter

Abstract

In this paper, a subtractive clustering based type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic process is used as a fuzzy filter to treat acceleration data for the purpose of obtaining the rigid-body dynamical parameters of robotic manipulators. Experimental results show the effectiveness of this method, which not only provides good accuracy of prediction of the rigid-body dynamical parameters of robotic manipulators, but also assesses the uncertainties associated with the modeling process and with the outcome of the model itself. A comparison of the results from the type-2 fuzzy logic filtering algorithm with its type-1 counterpart is presented and limitation of those methods is discussed.