Abstract:

For unmeasured fault parameter estimation of nonlinear system, a state and parameter joint estimation algorithm based on multiple fading factors strong tracking square-root cubature Kalman filter (MSTSCKF) is presented. Under the basic theory framework of strong tracking filter, MSTSCKF introduces the multiple fading factors to adjust gain matrix in real time and avoids the problem that square-root cubature Kalman filter (SCKF) decreases in accuracy and even diverges when the changing function of fault parameters is unknown or fault parameters abruptly change. Meanwhile, MSTSCKF combines high nonlinear curve fitting and numerical stability of SCKF. The simulation results indicate that higher estimation accuracy is obtained compared with SCKF and strong tracking unscented Kalman filter (UKF).