Secure finite-time filtering for switched fuzzy systems with scaling attacks and stochastic sensor faults

Abstract

In this study, we introduce a design for robust secure finite-time mixed H ∞ and passivity filter for discrete-time switched fuzzy systems. This design effectively combats both stochastic scaling attacks and sensor failure. To be specific, the sensor signals are represented by stochastic variables with different failure rates. Also, a comprehensive model is presented to characterize the scaling attacks and it is described by the Bernoulli distributed random variable. By designing a suitable Lyapunov functional candidate and leveraging the principles of finite-time theory, we have formulated a new collection of sufficient conditions. These conditions, expressed as linear matrix inequalities, ensure that the augmented fuzzy system maintains robust stochastic finite-time boundedness, along with a predetermined mixed H ∞ and passivity performance index. Ultimately, two numerical demonstrations are provided, incorporating real-world applications from the continuous-time single-link robot arm model and the tunnel diode circuit systems, to highlight the practicality of the proposed secure filter design.