Adaptive fuzzy filtering for multi-area power systems subject to nonhomogeneous sojourn probabilities

Abstract

This paper focuses on the design of an adaptive fuzzy filter for discrete-time multi-area power systems, considering the presence of sojourn probabilities and deception attacks. To capture the dynamic behavior of multi-area power systems more accurately, an innovative switching law is introduced, incorporating nonhomogeneous sojourn probability information. The feedback sojourn probability information is determined by a deterministic switched signal, enhancing the system's stability and performance. With the aim of addressing the potential impact of measurement outlier, a robust filter is developed, incorporating a dynamic saturation constraint and fuzzy logic systems. The filter effectively mitigates the influence of outliers by adaptively adjusting the saturation level based on estimation errors. The stability analysis is carried out using Lyapunov theory and average dwell-time information, demonstrating the mean square exponentially ultimately bounded of the augmented system. To validate the proposed algorithm, a simulation example is presented, showcasing its effectiveness and practical applicability in real-world scenarios.