Details

Autor(en) / Beteiligte

• Li, Xiao-Jian
• Shen, Xin-Yu

Titel

A Data-Driven Attack Detection Approach for DC Servo Motor Systems Based on Mixed Optimization Strategy

Ist Teil von

• IEEE transactions on industrial informatics, 2020-09, Vol.16 (9), p.5806-5813

Ort / Verlag

Piscataway: IEEE

Erscheinungsjahr

2020

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• This article is concerned with the data-driven attack detection problem for cyber-physical systems with the actuator attacks and measurement noise. In most of existing data-driven detection methods, <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> index is used to characterize the sensitivity performance. It is well-known that compared with the <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> index, <inline-formula><tex-math notation="LaTeX">H_-</tex-math></inline-formula> index can significantly improve the diagnostic performance. However, the detection system design based on the <inline-formula><tex-math notation="LaTeX">H_-/H_\infty</tex-math></inline-formula> mixed optimization technique has not been solved within the data-driven framework. In this article, a residual generator is constructed from the available input-output (I/O) data. <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">H_-</tex-math></inline-formula> indices are defined from the viewpoint of time-domain to characterize the robustness of residual generator against measurement noise and sensitivity to attack signals, respectively. In particular, a novel weighting system, which is expressed as an I/O model, is designed to transform the <inline-formula><tex-math notation="LaTeX">H_-</tex-math></inline-formula> performance into an <inline-formula><tex-math notation="LaTeX">H_\infty</tex-math></inline-formula> constraint, and the detection system design problem based on <inline-formula><tex-math notation="LaTeX">H_-/H_\infty</tex-math></inline-formula> mixed optimization technique is finally formulated into a constraint-type optimization one, which can be solved by the classical Lagrange multiplier method. Also, the proposed detection method is applied to a networked dc servo motor system to verify its advantages and effectiveness.