论文信息 - Numerically robust implementation of multiple-model algorithms

Numerically robust implementation of multiple-model algorithms

Standard implementation of multiple-model (MM) estimation algorithms may suffer from numerical problems, especially numerical underflows, which occur when the true model is vastly different from one or more models used in the algorithm. This may be devastating to the performance of the MM algorithm. Numerical robust implementations of some of the most popular MM algorithms are presented. Simulation results are provided to verify the proposed implementation and to compare with the implementations with a lower bound.

Youmin Zhang | X. Rong Li | Youmin Zhang | X. Li

[1] Herbert Rauch,et al. Fault detection, isolation, and reconfiguration for aircraft using neural networks , 1993 .

[2] D. Magill. Optimal adaptive estimation of sampled stochastic processes , 1965 .

[3] Murat Efe,et al. The IMM Approach to the Fault Detection Problem , 1997 .

[4] Youmin Zhang,et al. Detection and diagnosis of sensor and actuator failures using IMM estimator , 1998 .

[5] Y. Bar-Shalom,et al. The interacting multiple model algorithm for systems with Markovian switching coefficients , 1988 .

[6] Peter S. Maybeck,et al. Performance enhancement of a multiple model adaptive estimator , 1995 .

[7] Peter S. Maybeck,et al. Sensor/actuator failure detection in the Vista F-16 by multiple model adaptive estimation , 1995 .

[8] Amir Averbuch,et al. Interacting Multiple Model Methods in Target Tracking: A Survey , 1988 .

[9] Raman K. Mehra,et al. Failure Detection and Identification Using a Nonlinear Interactive Multiple Model (IMM) Filtering Approach with Aerospace Applications , 1997 .