How to cope with unmeasurable premise variables in Takagi-Sugeno observer design: Dynamic extension approach

Abstract : In this paper, a new strategy to cope with unmeasurable premise variables in observer design for Takagi-Sugeno (TS) models is proposed. The guiding principles are the immersion techniques and auxiliary dynamics generation, allowing to immerge a given TS system with unmeasured state dependent weighting functions into a larger TS system with weighting functions depending only on measured variables. This result relaxes the strong conditions used in the design of observers for TS systems with unmeasurable premise variables. An example is provided to illustrate the performances of the proposed approach.
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Dalil Ichalal, Benoît Marx, Saïd Mammar, Didier Maquin, José Ragot. How to cope with unmeasurable premise variables in Takagi-Sugeno observer design: Dynamic extension approach. Engineering Applications of Artificial Intelligence, Elsevier, 2018, 67, pp.430-435. ⟨10.1016/j.engappai.2017.09.018⟩. ⟨hal-01609899⟩

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