Robust composite adaptive fuzzy identification and control for a class of MIMO nonlinear systems

Abstract

A robust adaptive fuzzy identification and trajectory tracking control approach is developed for a class of multi-input-multi-output (MIMO) nonlinear systems in the presense of unmodeled uncertainties, parametric uncertainties, and external disturbances. A sliding mode-based fuzzy model identification/observer method is used to provide additional feedback of the unknown system dynamics. The model identification error is used along with the tracking error as a composite adaptive update law for a fuzzy logic based feedforward term. The fuzzy logic feedforward term is used in conjunction with a recently developed robust integral of the sign of the error (RISE) feedback method to yield a continuous controller that achieves semi-global asymptotic trajectory tracking.