Adaptive fuzzy-neural sliding mode control for a class of uncertain nonlinear dynamical systems

[[abstract]]In this paper, a novel design algorithm of adaptive fuzzy-neuralsliding mode control for a class of uncertain nonlinear dynamicalsystems is proposed to attenuate the effects caused by unmodeleddynamics, disturbances and approximate errors. Since fuzzy-neuralsystems can uniformly approximate nonlinear continuous functions toarbitrary accuracy, the adaptive fuzzy control theory is employed toderive the control law for a class of nonlinear system, with unknownnonlinear functions and disturbances. Moreover, the sliding modecontrol method is incorporated into the control law so that thederived controller is robust with respect to unmodeled dynamics,disturbances and approximate errors. To demonstrate the effectivenessof the proposed method, an example is illustrated in this paper.