Adaptive H∞ RBFN tracking control for nonlinear systems with unknown hysteresis

A radial basis function network (RBFN) based adaptive H^∞ control scheme for nonlinear systems with unknown hysteresis nonlinearity is developed. This scheme applies the method of pseudo-control to the design of the control strategy for the systems with hysteresis that cannot be measured directly. For the uncertainty of unknown hysteresis, the H^∞ optimal control technique based on RBF neural network is utilized. Therefore, the tracking error of the system is suppressed to a prescribed small region. Finally, the effectiveness of the proposed control scheme is illustrated through simulation.