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2008

Robust neuro-identification of nonlinear plants in electric power systems with missing sensor measurements

11 years 7 months ago
Robust neuro-identification of nonlinear plants in electric power systems with missing sensor measurements
Fault tolerant measurements are an essential requirement for system identification, control and protection. Measurements can be corrupted or interrupted due to sensor failure, broken or bad connections, bad communication, or malfunction of some hardware or software. This paper proposes a novel robust artificial neural network identifier (RANNI) by combining a sensor evaluation and (missing sensor) restoration scheme (SERS) and an ANN identifier (ANNI) in a cascading structure. This RANNI is able to provide continuous on-line identification of nonlinear plants when some crucial sensor measurements are unavailable. A static synchronous series compensator (SSSC) connected to a power system is used as a test system to examine the validity of the proposed model. Simulation studies are carried out with single and multiple phase current sensors missing; results show that the proposed RANNI continuously tracks the plant dynamics with good precision during the steady state, the small disturban...
Wei Qiao, Zhi Gao, Ronald G. Harley, Ganesh K. Ven
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where EAAI
Authors Wei Qiao, Zhi Gao, Ronald G. Harley, Ganesh K. Venayagamoorthy
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