标题： 使用快速自适应未知输入观测器估计故障/攻击：一种增强的LMI方法 显示英文标题

标题： Estimating the Faults/Attacks using a Fast Adaptive Unknown Input Observer: An Enhanced LMI Approach

摘要： 本文研究了在传感器故障和执行器故障影响下，Lipschitz非线性系统的鲁棒故障估计问题。在所提出的方法中，通过将传感器故障向量与系统状态相结合，构建了一个描述器系统。提出了一种新颖的快速自适应未知输入观测器（FAUIO）结构，用于同时估计一类非线性系统的故障和状态。通过利用$\mathcal{H}_\infty$准则，建立了一个新的LMI条件，以确保所设计观测器的估计误差的渐近收敛性。该导出的LMI条件是通过结合重新表述的Lipschitz性质、一种新的Young不等式变体以及众所周知的线性参数变化（LPV）方法推导出来的。它比文献中的现有方法更为宽松，并将其有效性与其他提出的方案进行了比较。此外，所提出的观测器方法被扩展用于受干扰影响的非线性系统，以实现状态和故障的重构并具有最优噪声衰减。随后，通过在MATLAB Simulink中应用单连杆机械臂操作器对两种设计方法进行了验证。 显示英文摘要

摘要： This paper deals with the problem of robust fault estimation for the Lipschitz nonlinear systems under the influence of sensor faults and actuator faults. In the proposed methodology, a descriptor system is formulated by augmenting sensor fault vectors with the states of the system. A novel fast adaptive unknown input observer (FAUIO) structure is proposed for the simultaneous estimation of both faults and states of a class of nonlinear systems. A new LMI condition is established by utilizing the $\mathcal{H}_\infty$ criterion to ensure the asymptotic convergence of the estimation error of the developed observer. This derived LMI condition is deduced by incorporating the reformulated Lipschitz property, a new variant of Young inequality, and the well-known linear parameter varying (LPV) approach. It is less conservative than the existing ones in the literature, and its effectiveness is compared with the other proposed approaches. Further, the proposed observer methodology is extended for the disturbance-affected nonlinear system for the purpose of the reconstruction of states and faults with optimal noise attenuation. Later on, both designed approaches are validated through an application of a single-link robotic arm manipulator in MATLAB Simulink.