Robust adaptive fuzzy-neural control of nonlinear dynamical systemsusing generalized projection update law and variable structurecontroller

摘要

In this paper, a robust adaptive fuzzy-neural control scheme fornnonlinear dynamical systems is proposed to attenuate the effects causednby unmodeled dynamics, disturbance, and modeling errors. A generalizednprojection update law, which generalizes the projection algorithmnmodification and the switching-Σ adaptive law, is used to tune thenadjustable parameters for preventing parameter drift and confiningnstates of the system to the specified regions. Moreover, a variablenstructure control method is incorporated into the control law so thatnthe derived controller is robust with respect to unmodeled dynamics,ndisturbances, and modeling errors. To demonstrate the effectiveness ofnthe proposed method, several examples are illustrated in thisnpaper