Comparison of Parameter and State Estimation Based FDI Algorithms

Abstract The similarities and differences between parameter estimation and state observation based Fault Detection and Isolation (FDI) techniques have been examined in this paper from an analytic point of view. The schemes considered are Recursive Least Squares (RLS) based parameter estimation algorithms, observer and/or Kalman filter based state estimation techniques. The comparison criteria used in the paper are the rate of convergence (related to fault detection delay), the fault isolability, the requirements on the richness of the system input, as well as the complexities of the algorithms at the time of implementation. It is concluded that both parameter estimation and state estimation based FDI schemes have their own special features. It is also very interesting to know that the features associated with the different approaches are complementary to each other. In some applications, one may have to use both to take full advantage of the given situation.

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