Secure Dynamic Output Feedback Control of Fuzzy Multi-Rate Systems Under Important Data-Based Attacks

This paper investigates the resilient dynamic feedback control problem for fuzzy multi-rate systems (FMRS) subject to a novel important-data-based attack (IDBA). In practical engineering systems, physical limitations such as sensor aging, quantization effects, and unstable power supplies often cause discrepancies between measurement outputs and actual system states, leading to multi-rate sampling behaviors. To accurately characterize such sampling inconsistencies, a nonhomogeneous Markov sampling model is introduced, which provides a more realistic description and reduces conservatism compared with traditional homogeneous models. Motivated by the need for stealthy yet destructive cyber attacks, this paper further proposes an IDBA scheme, in which the adversary selectively identifies and disrupts only the most critical data nodes based on their instantaneous impact on system behavior. To mitigate the severe disruptions caused by IDBA, a resilient dynamic output feedback controller is designed, thereby enhancing adaptability under adverse network conditions. Simulation studies, including both numerical and practical examples, demonstrate that the proposed control framework effectively preserves system stability and achieves superior performance in the presence of IDBA.