This study presents the design of a fault detection and diagnosis (FDD) scheme, composed from a bank of two types of observers, applied to linear parameter varying (LPV) systems. The first one uses a combination of reduced-order LPV observers to detect, isolate and estimate actuators faults, and the second one consists of a set of full-order LPV unknown input observers (UIO) to detect, isolate and estimate sensors faults. The observers’ design, convergence and its stability conditions are guaranteed in terms of linear matrix inequalities (LMI). Therefore, the main purpose of this work is to provide a novelty model-based observers’ technique to detect and diagnose faults upon non-linear systems. Simulation results, based on two typical chemical industrial processes, are given to illustrate and discuss the implementation and performance of such an approach.

这项研究提出了一种故障检测与诊断（FDD）方案的设计，该方案由一组两种类型的观察者组成，应用于线性参数变化（LPV）系统。第一个使用降阶LPV观测器的组合来检测，隔离和估计执行器故障，第二个使用一组全阶LPV未知输入观测器（UIO）来检测，隔离和估算传感器故障。观察者的设计，收敛性及其稳定性条件通过线性矩阵不等式（LMI）得到保证。因此，这项工作的主要目的是提供一种基于新颖模型的观察者技术来检测和诊断非线性系统上的故障。基于两个典型的化学工业过程的仿真结果，