Finite-Time Stability for Fuzzy Systems: A Weighted Sum-Based Dynamic Event-Triggered Mechanism

In Takagi-Sugeno (T-S) fuzzy systems, the design of Dynamic Output Feedback Controller (DOFC) plays a crucial role in ensuring system performance. However, traditional DOFC designs often rely on instantaneous samples, which may lead to suboptimal stability and fail to leverage historical system information effectively. To address the above limitation, we propose a novel Weighted Sum-based Dynamic Event-Triggered Mechanism (WSDETM) for T-S fuzzy system that incorporates weighted historical measurement samples and internal dynamic variables to enhance the triggering condition. By considering the relative importance of past samples, the design of controller can achieve faster convergence to the equilibrium point, resulting in ensuring finite-time stability. In contrast to traditional DOFC designs focusing on asymptotic Lyapunov stability, our approach prioritizes finite-time performance, which is crucial for practical applications. Additionally, deception attacks are modelled in the system as a Markov random process, providing a more general and robust framework compared to the traditional Bernoulli process. The design of DOFC and WSDETM parameters is achieved using the cone complementarity linearization algorithm, and extensive experimental results demonstrate the superior performance of WSDETM in terms of stability, finite-time convergence, and communication efficiency. Eventually, the main results demonstrate the superiority of WSDETM in two cases.