Adaptive parameter estimator based on T-S fuzzy models and its applications to indirect adaptive fuzzy control design (Q1827148)

The paper focuses on the use of continuous-time Takagi-Sugeno (T-S) fuzzy models in parameter estimation. The approach exploits the fact that a T-S fuzzy model of a plant represents a combination of several linear systems which is able to approximate nonlinear dynamics. The parameters are adjusted online, in accordance with a series-parallel estimation scheme whose properties are analyzed in terms of the Lyapunov theory. The proposed estimator can be incorporated into the structure of an indirect adaptive fuzzy controller. The applicability is illustrated by simulation experiments referring to the control of an inverted pendulum.