A fuzzy basis function vector-based multivariable adaptive controller for nonlinear systems.

In this paper, a new fuzzy basis function vector (FBFV) approach for the adaptive control of multivariable nonlinear systems is presented. With this method, the nonlinear plant is first linearized. The linearized bias and uncertainties as well as disturbances are assumed to be included in the model structure and their upper bound will be adaptively learned by the FBFV method. The output of the FBFV is used as the parameters of the robust controller in the sense that both the robustness and the asymptotic error convergence can be obtained for the multivariable nonlinear system. The effectiveness of the proposed analysis and design method is illustrated with a simulated example.