Exponential sampled-data fuzzy stabilization of nonlinear systems and its application to basic buck converters

This study focuses on the exponential stability and stabilization of nonlinear systems via fuzzy sampled-data control technique. The stability and stabilization conditions are obtained through constructing suitable Lyapunov functional which contains the sampling information and the solvable linear matrix inequalities. Then, the dynamics of the nonlinear buck converter system and Lorenz system with the sampled-data controller is analyzed and designed. Finally, the proposed method is validated with a basic buck converter system model designed to reflect the characteristics of the power metal-oxide-semiconductor field-effect transistors in the numerical section. In addition, the superiority of the sufficient conditions obtained is shown by comparing with the existing methods of the Lorentz system.