JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (5): 130-135.doi: 10.6040/j.issn.1672-3961.0.2017.252

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A fault detection and estimation scheme for nonlinear stochastic systems based on SCKF

LI Hongyang, HE Xiao*   

  1. Department of Automation, Tsinghua University, Beijing 100084, China
  • Received:2017-04-18 Online:2017-10-20 Published:2017-04-18

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Abstract: The fault detection and estimation problem was investigated for a class of nonlinear stochastic systems based on the square root cubature Kalman filter(SCKF). To estimate the states of complex nonlinear systems, SCKF has the outstanding characterizations of higher accuracy, better stability and lower computational burden. For nonlinear stochastic systems subject to actuator faults, the states were estimated based on the square root cubature Kalman filter. Moreover, according to the estimation results, a residual was designed by using the moving-horizon technique to detect the actuator fault. The faults were estimated based on a state augmentation method. A simulation experiment was given to verify the effectiveness of the proposed scheme.

Key words: fault detection, fault estimation, nonlinear stochastic systems, actuator faults, SCKF

CLC Number: 

  • TP206+.3
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