Robust Adaptive H_∞ Tracking Control Based on State Observer for a Class of Non-affine Nonlinear Systems

A robust adaptive H_∞ tracking control architecture with state observer is proposed for a class of nonaffine nonlinear systems.A Gauss radial basis function neural network(RBF neural network) is used to eliminate nonlinear modeling errors,and a high-gain observer is used to estimate the system output derivatives which are un-(available) for measurement.Lyapunov stability theory is used to derive the control laws including fixed control law and adaptive law,and the detailed analysis is given.It is shown that the tracking error is guaranteed to be asymptotically convergent to zero when there exists no externel disturbance,and a desired H_∞ tracking performance is achieved when externel disturbances exist.