Indirect fuzzy adaptive control: hyperstability approach

A new fuzzy indirect adaptive controller for continuous-time nonlinear systems, with a poorly understood dynamics, is developed. The proposed adaptive scheme uses a single Takagi-Seguno (TS) fuzzy model with few parameters to learn, which results in low implementation complexity and a fast learning rate. In addition, the use of TS fuzzy model permits the inclusion of a priori knowledge about the plant dynamics in terms of exact mathematical models or qualitative information. Using the hyperstability approach, it is proved that this adaptive controller is globally asymptotically stable, and achieves asymptotic tracking of a stable reference model. The performance of the developed approach is illustrated with simulation results.