This article undertakes the problem of simultaneous estimation of state and process faults in linear parameter varying systems. For this purpose, a novel strategy that exploits recent results on the design of observers for quadratic parameter varying systems is developed, and a complete design procedure is described. First, it is shown that by treating the process faults as additional states to be estimated, the arising augmented state-space model is indeed expressed as a quadratic parameter varying system. Hence, the estimates provided by a quadratic parameter varying observer based on the so-called linear output error injection principle would comprise both the actual state and the process faults estimates. Robust design conditions that minimize the effect of disturbances and measurement noise on some linear, and possibly parameter-varying, combination of error variables are obtained using a Lyapunov-based approach. Then, it is shown that the design problem can be reduced to a finite set of linear matrix inequalities that can be solved using available computational tools. The final part of the article exhibits an illustrative example, which clearly exposes the potential applicability and performance of the developed approach.

中文翻译：

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使用稳健的二次参数变化观测器在线性参数变化系统中同时进行状态和过程故障估计

本文承担了线性参数变化系统中状态和过程故障的同时估计问题。为此，开发了一种利用二次参数变化系统观测器设计的最新结果的新策略，并描述了完整的设计程序。首先，它表明通过将过程故障视为要估计的附加状态，产生的增强状态空间模型确实表示为二次参数变化系统。因此，由基于所谓的线性输出误差注入原理的二次参数变化观测器提供的估计将包括实际状态和过程故障估计。稳健的设计条件，可最大限度地减少干扰和测量噪声对某些线性且可能随参数变化的影响，使用基于李雅普诺夫的方法获得误差变量的组合。然后，它表明设计问题可以简化为一组有限的线性矩阵不等式，可以使用可用的计算工具解决这些问题。文章的最后一部分展示了一个说明性示例，它清楚地展示了所开发方法的潜在适用性和性能。