Multivariable fuzzy adaptive

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dc.contributor.authorGoléa, Noureddine
dc.contributor.authorGoléa, Amar
dc.date.accessioned2022-04-27T03:31:39Z
dc.date.available2022-04-27T03:31:39Z
dc.date.issued2002
dc.description.abstractBased 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.ar
dc.identifier.urihttp://hdl.handle.net/123456789/12958
dc.language.isoenar
dc.subjectFuzzy systemsar
dc.subjectAdaptive controlar
dc.subjectReference modelar
dc.subjectStabilityar
dc.titleMultivariable fuzzy adaptivear
dc.title.alternativecontrol of nonlinear systemsar
dc.typeArticlear
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