LAUSR

This paper is concerned with the data-driven realization of fault detection approach with performance optimization. For our purpose, the data-driven realization form of linear kernel representations is studied first, which is essential in our work. It is followed by a data-driven realization of kernel representation and its implementation in the design scheme of fault detection systems. Nevertheless, the basic idea behind this approach lies in the one-step identification of kernel representation using LQ-decomposition. Then, the recursive kernel representation is introduced and the so-called gradient descent algorithm is applied to optimize the performance of the proposed data-driven fault detection system. The effectiveness of the proposed approaches is illustrated by a numerical example and a case study on laboratory setup of a three-tank system. This article is protected by copyright. All rights reserved