Privacy-Preserving Control for 2-D Systems With Guaranteed Probability
针对二维系统，提出一种基于异或逻辑和动态编解码的隐私保护机制，将传输数据压缩加密为有限比特密文，并设计控制器同时保证概率约束、均方有界性和隐私性能。
This article addresses the privacy-preserving control issue for two-dimensional systems with probabilistic constraints. According to the exclusive or logical operation and the dynamic coding–decoding rule, a privacy-preserving mechanism (PPM) is developed, under which the transmitted data is efficiently compressed and encrypted into a ciphertext with finite bits. A PPM-based controller is designed that simultaneously guarantees a prescribed probabilistic constraint, mean-square boundedness, and privacy performance. Mathematical techniques, including mathematical induction, Chebyshev inequality, and matrix analysis, are employed to establish sufficient conditions for the presence of the desired controller gains. Additionally, the privacy and secrecy performance of the PPM is analyzed and simulation examples are presented to showcase the efficacy of the proposed controller design method.