Indirect fuzzy adaptive control
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Date
2002
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
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 piant dynamics in terms of exact mathematical
models or qualitative information. Using the hyperstahility
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.
Description
Keywords
Fuzzy systems, Adaptive control, Hyperstability, Robustness