This article investigates the attack detection problem for linear parameter-varying (LPV) systems with unknown but bounded (UBB) noise, which are subject to multiple attacks. Traditionally, the control problems of LPV systems involve the introduction of the one-order free-weighting matrix (OOFWM) method, which is conservative and inevitably reduces the accuracy of estimation. In such cases, the SHOFWM method is proposed to address the conservatism problem. To be specific, the developed method exploits the parameter information inherent in the system and designs a more flexible free-weighting matrix. By further incorporating a switching mechanism, the SHOFWM method enables more degrees of freedom in calculating the constraint sets. This allows for relaxed conditions when determining the radius of constraint sets. Therefore, the constraint sets can be smaller, resulting in higher accuracy. Furthermore, an improved zonotope-based set-membership attack detection method is proposed. By utilizing the detection algorithm, it is possible to detect multiple attacks. Finally, the proposed methods are validated via two examples.

中文翻译：

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基于切换式方案设计的LPV系统在多重攻击下的宽松集合成员估计和网络攻击检测

本文研究了具有未知但有界 (UBB) 噪声的线性参数变化 (LPV) 系统的攻击检测问题，该系统会受到多种攻击。传统上，LPV系统的控制问题涉及引入一阶自由权矩阵（OOFWM）方法，该方法比较保守，不可避免地降低了估计的准确性。在这种情况下，SHOFWM方法被提出来解决保守性问题。具体来说，所开发的方法利用系统固有的参数信息并设计更灵活的自由权重矩阵。通过进一步结合切换机制，SHOFWM方法在计算约束集时具有更大的自由度。这在确定约束集的半径时允许宽松的条件。因此，约束集可以更小，从而获得更高的精度。此外，提出了一种改进的基于zonotope的集合成员攻击检测方法。通过利用检测算法，可以检测多种攻击。最后，通过两个例子对所提出的方法进行了验证。