Sensor bias fault isolation in a class of nonlinear systems

• Published in: IEEE transactions on automatic control Vol. 50; no. 3; pp. 370 - 376
• Main Authors: Xiaodong Zhang, Parisini, T., Polycarpou, M.M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2005; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Computer science; control theory; systems; Control theory. Systems; Exact sciences and technology; Fault detection; Fault detection and approximation; Fault diagnosis; fault isolation; Monitoring; nonlinear adaptive estimator; Nonlinear systems; nonlinear uncertain systems; Robustness; sensor bias; Sensor phenomena and characterization; Sensor systems; Stability; Uncertain systems; Wireless sensor networks; Approximation; Bias; Measurement sensor; nonlinear adaptive estimator; Non linear control; nonlinear uncertain systems; Adaptive estimation; fault isolation; sensor bias; Uncertain system; Observer; Nonlinearity; Fault detection and approximation; Artificial intelligence; Fault diagnostic; Measurement error; Defect detection
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2005.843875

This note presents a robust fault isolation scheme for a class of nonlinear systems with sensor bias type of faults. The proposed fault diagnosis architecture consists of a fault detection estimator and a bank of isolation estimators, each corresponding to a particular output sensor. Based on the class of nonlinear systems and sensor bias faults under consideration, the stability and learning properties of the fault isolation estimators are obtained, adaptive thresholds are derived for the isolation estimators, and fault isolability conditions are rigorously investigated, characterizing the class of nonlinear faults that are isolable by the proposed scheme. A simulation example is used to illustrate the effectiveness of the sensor bias fault isolation methodology.