Cyber Attack Estimation for Intelligent Connected Vehicle

Detecting the cyber-attacks in intelligent connected vehicle systems (ICVS) precisely is essential for ensuring the personal security and normal communication of ICVS. This paper gives a solution to estimate cyber-attacks for ICVS. A distinctive approach is represented to take advantage of an augmented states technique of ICVS. What's more, a nonlinear fuzzy unknown input observer (FUIO) to estimate dynamics asymptotically of ICVS that is under cyber attacks is proposed. For the FUIO design, the dynamics model ICVS can be written in the particular Takagi-Sugeno (TS) fuzzy model in the form of nonlinear consequence. Particularly, the application of TS theory enables the implement of differential mean value theorem (DMVT), which attaches great importance to the simplification of perplexing premise variables that are unmeasured. Furthermore, a linear matrix inequalities is given by exploiting TS theory, which can not only satisfy the sufficient conditions of FUIO designing, but also be easily solved by a series of techniques such as convex optimization. The simulation figures demonstrate great effectiveness of the formulated FUIO design.