Title :
A sliding mode observer approach for fault detection and diagnosis in uncertain nonlinear systems
Author :
Ma, Liling ; Yang, Yinghua ; Wang, Fuli ; Lu, Ningyun
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Presents a sliding mode observer approach to fault detection and diagnosis for nonlinear systems with uncertainty having unknown bounds. The robustness properties of the observer ensure that no false alarms are registered due to uncertainties and disturbances in the system. The observer uses nonlinear gains that are smoothed versions of classical sliding mode gains and they are continuously updated to guarantee a globally stable observation error. A neural network is designed to capture the nonlinear characteristics of faults. Finally, simulation results have shown the feasibility and effectiveness of the method.
Keywords :
fault diagnosis; nonlinear control systems; observers; radial basis function networks; uncertain systems; variable structure systems; fault detection; fault diagnosis; globally stable observation error; neural network; nonlinear characteristics; nonlinear gains; robustness properties; sliding mode observer approach; uncertain nonlinear systems; Electrical equipment industry; Error correction; Fault detection; Fault diagnosis; Information science; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Robustness; Uncertainty;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1020009
