Output details
15 - General Engineering
University of Northumbria at Newcastle
Novel Parameter Identification by Using a High-Gain Observer With Application to a Gas Turbine Engine
This article presents a highly novel identification technique in order to bridge the gap between modeling and control issues by unifying noise assumptions. Adaptive parameters change detection and parameters identifications were proposed to update the on-line model and monitor abrupt parameter faults. This is the outcome of a NSFC (60574026) and EPSRC projects (EP/C015185/1). The work led to international collaborations with Abo Akademi University and Zhejiang University, resulting in a special issue of IEEE Transactions on Industrial Informatics (led by Gao, DOI: 10.1109/TII.2013.2281002 , Nov 2013) and two invited collaborative survey papers on data-driven modeling and fault diagnosis (10.1109/TII.2013.2243743, 10.1109/TII.2012.2226897).
