REDUCING THE GAP BETWEEN FUZZY AND NONLINEAR CONTROL

LMI formulations for fuzzy control became the tool of choice in the 1990s. Many nonlinear systems can be modelled as fuzzy systems (sector-nonlinearity), so fuzzy control may be considered as a technique for nonlinear control. Fruitful results have been obtained, but some sources of conservativeness remain when compared to other nonlinear approaches. This paper outlines such conservativeness issues (shadows), and discusses some ideas (lights) on overcoming them.