Quantized Stabilization for Discrete IT2 Fuzzy Semi-Markovian Switching Models under DoS Attacks

The article explores the advanced stabilization techniques for discrete interval type-2 (IT2) fuzzy semi-Markovian switching models (S-MSMs) under denial-of-service (DoS) attacks. It addresses the limitations of traditional Markovian switching models by incorporating semi-Markovian dynamics, which better capture the memory characteristics and general probability distributions of real-world systems. The research introduces a novel approach to quantized control, considering both signal quantization and network attacks, which are critical factors in modern networked control systems. By leveraging the semi-Markovian kernel (SMK) method and state-dependent Lyapunov functions, the article provides sufficient conditions for the existence of observer-based quantized controllers, ensuring mean-square stability. The practical relevance of the study is demonstrated through an example of a single-link robotic arm system, showcasing the effectiveness of the proposed methods in enhancing system robustness and performance under adverse conditions. The article also highlights the innovative aspects of the IT2 fuzzy model in handling parameter uncertainty and the integration of SMK theory for improved stability analysis.