Abstract
This paper outlines two contributions to stability analysis of fuzzy systems: knowledge of the membership function shape (actually, constraints on the membership function values) and polynomial approaches. Both ideas reduce the conservativeness in the stability analysis of a nonlinear system when expressed as a fuzzy model by using membership shape information and by allowing a more general class of “fuzzy” systems than the widely-used Takagi-Sugeno one with linear consequents. In this way, the gap between fuzzy and nonlinear control gets smaller.
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