Adaptive fuzzy observer and robust controller for a 2-DOF robot arm

Recently, adaptive fuzzy observers have been introduced that are capable of estimating uncertainties along with the states of a nonlinear system represented by an uncertain Takagi-Sugeno (TS) model. In this paper, we use such an adaptive observer to estimate the uncertainties in the state matrices of a two-degrees-of-freedom robot arm model. The TS model of the robot arm is constructed using the sector nonlinearity approach. The estimates are used in updating the model, and the updated model is used to design a controller for the robot arm. We analyze the improvement in the achievable controller performance when using the adaptive observer.