Controller Design for Takagi-Sugeno Fuzzy Systems with Nonlinear Consequent Part Via Sampled-Data Measurements

This paper investigates the controller design problem for a class of nonlinear systems by introducing a Takagi-Sugeno system with nonlinear consequent parts. In this regard, it is assumed that the measured variables are available at discrete-time instants with non-periodic sampling time. Using the Lyapunov-Krasovskii stability theory, some conditions are presented and expressed in the form of linear matrix inequalities such that the closed-loop system is asymptotically stable and achieves a prescribed H
_∞
performance level. Finally, a numerical examples is provided to illustrate the effectiveness of the proposed method.