The problem of fault estimation for nonlinear systems with Lipschitz nonlinearities is addressed in this work for the estimation of both the system fault and states. In the proposed approach disturbance is regarded to be a function which is nonlinear and coupled with states of the system, and fault to be a function which is additive. In order to diagnose the fault and reduce the disturbances effects by dissipativity theory, Luenberger and two unknown input observers (UIOs) are designed separately. If the system satisfies the matching condition, the first UIO can accurately estimate faults by decoupling the effects of state-coupled disturbances. Otherwise, the second UIO estimates faults by decoupling partial disturbances, and attenuating the disturbances which cannot be decoupled. The essential conditions for all designed observers to exist are stated. Finally, the suggested method is applied to a robot by simulation to analyse its performance.

在这项工作中解决了具有 Lipschitz 非线性的非线性系统的故障估计问题，用于估计系统故障和状态。在所提出的方法中，干扰被认为是一个与系统状态耦合的非线性函数，而故障被认为是一个可加的函数。为了通过耗散理论诊断故障并减少干扰影响，分别设计了 Luenberger 和两个未知输入观测器（UIO）。如果系统满足匹配条件，则第一个 UIO 可以通过解耦状态耦合扰动的影响来准确估计故障。否则，第二个 UIO 通过解耦部分干扰并衰减无法解耦的干扰来估计故障。陈述了所有设计观察者存在的基本条件。最后，通过仿真将所建议的方法应用于机器人以分析其性能。