Security Data-Driven Control for Nonlinear Systems Subject to Deception and False Data Injection Attacks
Wei Yu, Xuhui Bu, Zhongsheng Hou
Abstract
This paper studies the security data-driven control problem for a class of nonlinear systems with completely unknown dynamics under the deception attacks (DA) and false data injection attacks (FDIA) via faded channels. Firstly, the fading phenomenon is formulated by the Rice fading model, which obeys the Gaussian distribution with a known mathematical expectation and variance. DA could invert the direction of I/O data and FDIA may result in false injection data with zero-mean Gaussian white noise. Then, by employing the compact form dynamic linearization method, the security model free adaptive controller (MFAC) is designed, which does not involve the model or structure information of the system. Next, the system stability is analyzed, and the compensation scheme with an increasing gain is proposed to counteract the adverse effect brought by faded channels. A numerical simulation and a load frequency control (LFC) example for multi-area power systems illustrate the validity of the proposed schemes.