Multivariable fuzzy adaptive
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Date
2002
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Abstract
Ba~ed on Takagi-Seguno (TS) fuzzy eystems, we are used, this allows fast control update, which is limit
Present a direct fuzzy model-following adaptive control for factor for L~~~~~~~ approach is used
multivariable (MIMO) nonlinear systems. The use of the TS
8y6tems allows the inclusion of a priori information to establish the stability and robustness properties of the
in terms of qualitative knowledge about the plant operat- proposed fuzzy adaptive scheme, in presence of approxiing
peints or analytical conventional linear regulators. It is mation error, external disturbance and input gain variaproven,
using Lyapunov stability, that this adaptive scheme tion, ~h~ results, for a two-li* robot model, is robust against external disturbance, approximation error
and input gain variation, and achieves asymptotic tracking show that, this fuzzy adaptive control realizes a consistent
of a stable reference model. The effectiveness of the pro- tracking performance under approximation error and exterposed
fuzzy approach is demonstrated, by simulation, on a
two-link robot model.
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Keywords
Fuzzy systems, Adaptive control, Reference model, Stability