Encryption-decryption-based state estimation for nonlinear complex networks subject to coupled perturbation

• Published in: Systems science & control engineering Vol. 12; no. 1
• Main Authors: Gao, Peixia, Jia, Chaoqing, Zhou, Aozhan
• Format: Journal Article
• Language: English
• Published: Macclesfield Taylor & Francis 31.12.2024; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Algorithms; boundedness analysis; Communication; complex networks; coupled perturbation; Covariance; Difference equations; Encryption; encryption-decryption scheme; Parameter estimation; Perturbation; Random variables; State estimation; Upper bounds
• ISSN: 2164-2583; 2164-2583
• DOI: 10.1080/21642583.2024.2357796

This paper discusses the encryption-decryption-based state estimation (EDBSE) issue for coupled perturbation complex networks (CPCNs) in the framework of the Kalman-type filtering scheme. A uniform distributed random variable is employed to characterize the coupled perturbation among different network units. A uniform-quantization-dependent encryption-decryption (UQDED) scheme is considered here to orchestrate the transmitted data. A novel EDBSE approach is developed such that the upper bounds of prediction error (PE) covariance (PEC) and estimation error (EE) covariance (EEC) can be derived by resolving Riccati-like difference equations and the estimation parameter (EP) is determined by minimizing the trace of the upper bound of EEC. Furthermore, a uniformly bounded condition is elaborated to evaluate the algorithm performance of EDBSE. Finally, an illustrative example is conducted to verify the validity of the introduced EDBSE method.