Spatial basis functions based fault localisation for linear parabolic distributed parameter systems

作     者：Feng, Yun 

作者机构：Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hunan Univ Natl Engn Lab Robot Visual Percept & Control Tech Changsha 410082 Hunan Peoples R China 

出 版 物：《IET CONTROL THEORY AND APPLICATIONS》 (IET控制论与应用)

年 卷 期：2020年第14卷第20期

页      面：3580-3588页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0804[工学-仪器科学与技术] 0811[工学-控制科学与工程] 

主　　题：eigenvalues and eigenfunctions fault diagnosis reduced order systems distributed parameter systems differential equations linear parabolic distributed parameter systems fault localisation distributed residual signal approximated ordinary differential equation model higher-order models spatial basis functions reduced-order fault detection and localisation filter design spatial operator 

摘      要：Fault localisation for distributed parameter systems is as important as fault detection but is seldom discussed in the literature. The main reason is that an infinite number of sensors in the space are needed to construct a distributed residual signal, which is nearly impossible in practice. In this study, a fault detection and localisation filter which only uses a finite number of sensors is initiated based on an approximated ordinary differential equation model. Considering the limitations on computation resources for higher-order models in practice, a novel set of spatial basis functions is applied to the reduced-order fault detection and localisation filter design. Under certain conditions, the novel spatial basis functions obtain smaller state truncation error while the order is lower compared to the mostly used eigenfunctions of the spatial operator.