Abstract:
The work of this thesis focused on parametric identification of synchronous machine with salient poles (SG) equipped with
dampers of power 0.3kW.
First of all, they have been made in off-line mode from experimental tests according to international standards. For a more
precise determination of parameters in perturbed mode, we have developed on-line algorithms by applying different Kalman
Filters (KF) in continuous and discrete time: The Discrete Kalman Filter (DKF) is the applied estimator in this study because it
gives a good convergence compared to the real parameters; it is used in its various forms, traditional (TDKF) for linear systems
or in its extended form (DEKF) when the system is non-linear.
Another interesting application of DKF is when it is biased (DEKFB) because it will reduce the squared error (MSE) between
the measured and estimated values of the system state variable; as a result, the standardized MSE (NMSE) can be minimized.
Similarly, the standard deviation (STD) between the real and estimated values of the parameter can be limited to a tolerable
percentage.
The different KFs are implemented in a Matlab / Simulink environment in order to demonstrate the effectiveness of the DEKFB
estimator compared to other Filters. The simulation results are acceptable since a good match between the real and estimated
parameters has been obtained, which reflects the good noise filtering quality of the KF estimators designed and which can be
used in on -line parametric identification in disturbed mode of low scale generator.
