Abstract:

The multiple model adaptive estimation(MMAE) method has low capability to track abrupt faults, therefore multiple  fading factors may result in diverging the strong tracking filter(STF). Moreover, the fault probability calculation is large. An improved strong tracking multiple model adaptive estimation (STMMAE) fast diagnosis algorithm is proposed. The tracking performance of the filter is improved by multiple fading factors. An improved renewal equation of the step prediction covariance matrix is proposed. The stability of the filter is guaranteed, and the estimation accuracy is improved. Based on the Euclidean norm, a fast fault isolation method which reduces the fault probability calculation is proposed. The simulation results show that the proposed algorithm is more efficient and has a better performance.