This paper proposes a method for fault diagnosis of dynamic\ud processes using the multiple model approach. The technique\ud presented concerns the identification of a non--linear dynamic\ud system based on Takagi-Sugeno (TS) fuzzy models. It can be shown\ud that any non--linear dynamic process can, in fact, be described as a\ud composition of several TS models selected according to process\ud operating conditions. In particular, this work addresses a method\ud for the identification and the optimal selection of the local TS\ud models from a sequence of noisy input-output data acquired from the\ud process. The diagnostic scheme exploits the TS fuzzy models to\ud generate residuals. The developed technique was applied to the\ud fault diagnosis of the input--output sensors of an industrial gas\ud turbine and the results are also presented
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