The following study presents a novel fault detection approach, based on nonlinear parity design using nonlinear unknown input observers, for a class of nonlinear systems in the presence of sensor noise. Initially, fault and noise are decoupled via splitting the system into two subsystems by a series of transformations on the states and output equations. The nonlinear unknown input observer estimates the states in the subsystem subject to sensor noise, while the states in the other subsystem are estimated with the proposed equation. The objective in this study is to ensure the asymptotic stability of the error dynamics using the Lyapunov method. Hence, the results are formulated in the form of bilinear matrix inequalities. At the same time, the nonlinear parity approach is employed to design residue signals in the subsystem subject to actuator/component faults. Sufficient conditions are established to guarantee the convergence of the state estimation error. The goal in the parity approach is to generate a specific residue indicating the difference between nominal and faulty states. Finally, three simulations are provided to illustrate the efficiency of the proposed algorithm.

中文翻译：

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使用未知输入观测器的非线性系统故障检测的非线性奇偶校验方法

以下研究提出了一种新颖的故障检测方法，该方法基于使用非线性未知输入观测器的非线性奇偶校验设计，用于存在传感器噪声的一类非线性系统。最初，通过对状态和输出方程进行一系列变换，将系统分成两个子系统，从而将故障和噪声解耦。非线性未知输入观测器估计受传感器噪声影响的子系统中的状态，而另一个子系统中的状态则用所提出的方程估计。本研究的目的是使用李雅普诺夫方法确保误差动力学的渐近稳定性。因此，结果以双线性矩阵不等式的形式表述。同时，非线性奇偶校验方法用于设计子系统中受执行器/组件故障影响的残余信号。建立了足够的条件来保证状态估计误差的收敛。奇偶校验方法的目标是生成一个特定的残差，指示标称状态和故障状态之间的差异。最后，提供了三个仿真来说明所提出算法的效率。