Journal of Systems Engineering and Electronics ›› 2014, Vol. 25 ›› Issue (3): 496-501.doi: 10.1109/JSEE.2014.00057

• CONTROL THEORY AND APPLICATION • Previous Articles     Next Articles

Iterative learning based fault diagnosis for discrete linearuncertain systems

Wei Cao∗ and Ming Sun   

  1. College of Computer and Control Engineering, Qiqihar University, Qiqihar 161006, China
  • Online:2014-07-01 Published:2010-01-03


In order to detect and estimate faults in discrete linear time-varying uncertain systems, the discrete iterative learning strategy is applied in fault diagnosis, and a novel fault detection and estimation algorithm is proposed. And the threshold limited technology is adopted in the proposed algorithm. Within the chosen optimal time region, residual signals are used in the proposed algorithm to correct the introduced virtual faults with iterative learning rules, making the virtual faults close to these occurred in practical systems. And the same method is repeated in the rest optimal time regions, thereby reaching the aim of fault diagnosis. The proposed algorithm not only completes fault detection and estimation for discrete linear time-varying uncertain systems, but also improves the reliability of fault detection and decreases the false alarm rate. The final simulation results verify the validity of the proposed algorithm.