论文信息 - Neural networks-based scheme for system failure detection and diagnosis

Neural networks-based scheme for system failure detection and diagnosis

In this paper, the neural networks of fault tolerant control scheme in flight control is presented. The scheme can be broken up into three steps: fault detection, diagnosis, and accommodation. Particularly emphasis is placed on fault detection and diagnosis employing neural networks in this paper. The testing of the scheme is illustrated through F-16 aircraft model for an actuator failure.

Y. M. Chen | M. L. Lee

[1] Rolf Isermann,et al. Process fault detection based on modeling and estimation methods - A survey , 1984, Autom..

[2] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.

[3] A. Willsky,et al. Analytical redundancy and the design of robust failure detection systems , 1984 .

[4] John Moody,et al. Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.

[5] A. Willsky,et al. Failure detection and identification , 1989 .

[6] Mario Innocenti,et al. Fault detection using neural networks , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[7] Sukhan Lee,et al. A Gaussian potential function network with hierarchically self-organizing learning , 1991, Neural Networks.