Quantized sampled data control for finite time criteria of fuzzy system and its application to EPS model

This study presents a novel approach to reduce pressure ripples in electric power (EP) steering systems by proposing a quantized sampled-data controller (QSDC) based on the Takagi-Sugeno (T-S) fuzzy-model approach for finite-time extended dissipative analysis. With special consideration of the influence of velocity on EP steering control, a fuzzy QSDC is designed to actively mitigate the pressure ripple effects. By developing a novel Lyapunov-Krasovskii functional (LKF) that fully incorporates the characteristics of the sampled-data and utilizes integral inequalities, the study determines the extended dissipative performance in finite time for a certain class of EP systems with the QSDC. Utilizing the LKF, the study derives a stability criterion expressed in linear matrix inequalities using the MATLAB toolbox. Finally, simulation studies are performed to illustrate the efficacy and improved performance of the proposed methodology.