Robust adaptive fuzzy-neural control of nonlinear dynamical systems using generalized projection update law and variable structure controller

In this paper, a robust adaptive fuzzy-neural control scheme for nonlinear dynamical systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbance, and modeling errors. A generalized projection update law, which generalizes the projection algorithm modification and the switc hing-sigma adaptive law, is used to tune the adjustable parameters for prev enting parameter drift and confining states of the system to the specified regions. Moreover, a variable structure control method is incorporated into the control law so that the derived controller is robust with respect to u nmodeled dynamics, disturbances, and modeling errors. To demonstrate the ef fectiveness of the proposed method, several examples are illustrated in thi s paper.