Design of a static sliding mode controller for T-S fuzzy systems based on Quantized information

Abstract This study introduces a novel sliding mode control method that combines generalized T-S fuzzy systems and quantized feedback to enhance control efficiency and robustness in complex systems. Existing methods often perform poorly in environments with incomplete information and system uncertainties, making them ill-suited to the dynamic characteristics of complex systems. To address this issue, we propose a sliding mode control method that incorporates both static and dynamic quantizers (with adjustable quantization parameters). Our approach employs a sliding mode variable structure controller designed with traditional linear switching surfaces to ensure that the system approaches the desired sliding mode surface, thereby enhancing the asymptotic stability of the closed-loop system. This quantized feedback sliding mode control strategy effectively ensures the stability and robustness of generalized T-S fuzzy systems under conditions of incomplete information and system uncertainties. Simulation results demonstrate that the system exhibits good control performance under experimental conditions. In summary, our research provides an effective improvement, enhancing the adaptability of generalized T-S fuzzy systems in complex real-world environments and laying a solid foundation for future applications and expansions.