Relaxed state estimation of discrete-time nonlinear control systems via an improved fuzzy partition-based switching observer

Abstract The problem of relaxed state estimation of a class of discrete-time nonlinear plants is studied by developing an improved fuzzy partition-based switching observer. By introducing a pair of weighted scalars, the whole interval spanned by all the normalized fuzzy weighting functions at the present sampling instant is delimited as some non-overlapping sub-intervals. Then, an available fuzzy switching observer can be designed with all kinds of possible switching modes. Because much more information for each partition sub-interval could be considered in its activated switching mode, the obtained method can be less conservative than the existing methods reported in recent references. Finally, two illustrative simulations are given for testing the superiority of the proposed method over previous ones.

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