Fault diagnosis for sensors in a class of nonlinear systems

作者：Guo, Run-Xia^*; Guo, Kai; Dong, Jian-Kang

来源：IMA Journal of Mathematical Control and Information, 2018, 35(2): 375-391.

DOI：10.1093/imamci/dnw053

• sensors
• fault diagnosis
• state observer
• adaptive control
• nonlinear systems

Sensors are important parts of various control systems and their faults can cause degradation of systems. The problem of fault diagnosis for sensors is considered specially in this article. A time-varying and anti-disturbance fault diagnosis algorithm based on the fault detection observer and the adaptive control theory has been proposed for a class of nonlinear systems that are influenced by disturbances and measurement noise. When external disturbances, measurement noise and faults of sensors exist simultaneously, the designed fault diagnosis algorithm is able to give specific estimated values of state variables and faults, respectively. The asymptotical stability of the fault detection observer in the diagnosis algorithm for sensors is guaranteed by setting a well-designed adaptive adjusting law of the fault vector. Moreover, a theoretically rigorous proof based on Lyapunov stability theory has been given. Two experiments have been carried out to evaluate the performance of the proposed fault diagnosis algorithm.

• 出版日期2018-6
• 单位中国民航大学