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Mathematical Problems in Engineering
Volume 2015, Article ID 676289, 10 pages
Research Article

A Novel Strong Tracking Fault Prognosis Algorithm

Unit 302, Xi’an Research Institute of High-Tech, Xi’an 710025, China

Received 27 November 2014; Revised 21 December 2014; Accepted 21 December 2014

Academic Editor: Gang Li

Copyright © 2015 Qi Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Improving the ability to track abruptly changing states and resolving the degeneracy are two difficult problems to particle filter applied to fault prognosis. In this paper, a novel strong tracking fault prognosis algorithm is proposed to settle the above problems. In the proposed algorithm, the artificial immunity algorithm is first introduced to resolve the degeneracy problem, and then the strong tracking filter is introduced to enhance the ability to track abruptly changing states. The particles are updated by strong tracking filter, and better particles are selected by utilizing the artificial immune algorithm to estimate states. As a result, the degeneracy problem is resolved and the accuracy of the proposed fault prognosis algorithm is improved accordingly. The feasibility and validity of the proposed algorithm are demonstrated by the simulation results of the standard validation model and the DTS200 system.