Abstract: A robust adaptive tracking control method k presented based on T-S fuzzy model. The overall control scheme is constructed by combining all local state feedback controllers and robust adaptive neural network based controllers. By the proposed fuzzy adaptive robust: controller there is no need to find a comrnon positive definite matrix satisfying matrix Lyapunov equation. and no constraint or matching conditions are required. The learning ability of the proposed full adaptive RBF neural network with compensating component is improved through adaptive tuning of the weights, centers and widths on line. The adaptive compensating component is designed to compensate the shortcoming of the neural network through online estimating the bound Oil the neural network approximate error. With the proposed method, the stability of the closed-loop system is guaranteed and improved robustness and tracking performance are obtained．Simulation example is given to illustrate the effectiveness of the proposed method.