Stealthy Measurement-Aided Pole-Dynamics Attacks With Nominal Models
针对传统极点动力学攻击因模型失配而失去隐蔽性的问题，提出一种仅需测量数据的自适应控制攻击方法，在保持隐蔽性的同时实现类似破坏效果，并通过倒立摆实验验证。
When traditional pole-dynamics attacks (TPDAs) are implemented with nominal models, model mismatch between exact and nominal models often affects their stealthiness, or even makes the stealthiness lost. To solve this problem, this article presents a novel stealthy measurement-aided pole-dynamics attacks (MAPDAs) method with model mismatch. First, the limitations of TPDAs using exact models are revealed. Second, to handle the limitations, the proposed MAPDAs method is designed by using an adaptive control strategy, which can keep the stealthiness. Moreover, it is easier to implement as only the measurements are needed in comparison with the existing methods requiring both measurements and control inputs. Third, the performance of the proposed MAPDAs method is explored using convergence of multivariate measurements, and MAPDAs with model mismatch have the same stealthiness and similar destructiveness as TPDAs. Finally, experimental results from a networked inverted pendulum system confirm the feasibility and effectiveness of the proposed method.