Observer-based robust adaptive interval type-2 fuzzy tracking control of multivariable nonlinear systems

In this paper, in order to deal with training data corrupted by noise or rule uncertainties, a new observer-based indirect adaptive interval type-2 fuzzy controller is developed for nonlinear MIMO systems involving external disturbances using fuzzy descriptions to model the plant. Based on the universal approximation theorem, a fuzzy logic controller equipped with a training algorithm is proposed such that the tracking error, because of the matching error and external disturbance, is attenuated to an arbitrary desired level using the H∞ tracking design technique. Simulation results show that the interval type-2 fuzzy logic system can handle unpredicted internal disturbances—data uncertainties, very well, but the adaptive type-1 fuzzy controller must expend more control effort in order to handle noisy training data. In the meantime, the adaptive fuzzy controller can perform successful control and guarantee that the global stability of the resulting closed-loop system and the tracking performance can be achieved.