Reliable sampled-data fuzzy control for nonlinear systems

This study seeks to provide solutions to the main challenges that arise when dealing with non-linear systems, including uncertainty, external disturbances, and actuator failures. It focuses on solving the reliable sampled-data control problem by proposing a fuzzy output feedback control procedure for nonlinear systems prone to external disturbances and failures of actuators. In this study, the actuator fault model that involves linear and nonlinear terms is adopted, and a reliable sampled-data fuzzy static output feedback (SOF) controller is designed. Based on an appropriate Lyapunov-Krasovskii functional, delay-dependent sufficient conditions are established such that the closed-loop system is stable with a gamma level of H-infinity, performance against external disturbances. Furthermore, using the decoupling matrix procedure, a set of linear matrix inequalities (LMIs) is formulated to synthesize the controller gains. Finally, The theoretical developments are illustrated through numerical simulations cornering the stability of the vehicle lateral dynamics and the stabilization of Lorenz chaotic system.