Nonlinear output regulation via Takagi-Sugeno fuzzy mappings: A full-information LMI approach

Trajectory tracking has been long ago set into a formal mathematical framework through the nonlinear output regulation theory. Results thereby derived have been hardly implemented in a systematic way due to their complexity, which forces the designer to lead with expressions which are not necessarily computationally tractable. Fuzzy regulation has intended to fill this gap by introducing systematic procedures based on Takagi-Sugeno models and linear matrix inequalities. This paper offers a systematic approach to solve the nonlinear output regulation problem via state feedback and convex representations of the required mappings; in contrast with former results, this one takes full advantage of the time-derivatives of the membership functions. Moreover, it is fully based on element-wise linear matrix inequalities which are numerically solvable by interior-point-based methods.