Abstract
The problem of fault isolation (FI) for a kind of nonlinear discrete time varying (NDTV) systems is investigated. A bank of adaptive observers are designed for the considered system with different potential faults, and the isolation work is transformed into finding out which observer matches the current system best. The idea of reconstruction-based contribution (RBC) analysis is introduced to construct indicator variables for all of the observers and the one with the largest indicator variable is declared as the isolation result. In this method, knowledge of the system model is fully used, while the idea of contribution analysis is typically data-driven. Finally, simulation study is carried out with a nonlinear unmanned aerial vehicle (UAV) model, and the results demonstrate that the proposed method provides us with a new promising strategy for FI.
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