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 ad aptive control of multivariable nonlinear systems is presented. With this m ethod, the nonlinear plant is first linearized. The linearized bias and unc ertainties as well as disturbances are assumed to be included in the model structure and their upper bound will be adaptively learned by the FBFV meth od. The output of the FBFV is used as the parameters of the robust controll er in the sense that both the robustness and the asymptotic error convergen ce can be obtained for the multivariable nonlinear system. The effectivenes s of the proposed analysis and design method is illustrated with a simulate d example.