Adaptive fuzzy internal model control |
Posted on:2005-09-13 | Degree:M.S | Type:Thesis |
University:King Fahd University of Petroleum and Minerals (Saudi Arabia) | Candidate:Widodo, Agus Rohmat | Full Text:PDF |
GTID:2458390008483168 | Subject:Engineering |
Abstract/Summary: | |
The Internal Model Control (IMC) structure is composed of the explicit model of the plant and a stable feed forward controller. The major task for the IMC design is to find a precise model of the plant. In this work Takagi-Sugeno fuzzy modeling is used to approximate nonlinear systems. Modeling by linearization is employed at certain operating points and separate local linear models are obtained. The Takagi-Sugeno fuzzy model is constructed to fuzzily switch among the local linear models. In order to obtain a more precise model, a normalized least mean square algorithm is added in parallel to the fuzzy model to adaptively quanta for the model mismatch. An adaptive inverse control concept using adaptive finite-impulse-response (FIR) filters has been used to implement the feedforward-controller part of the IMC structure. |
Keywords/Search Tags: | Model, IMC, Adaptive, Fuzzy |
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