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It is found that, the PlO-like fuzzy logic controller is much less sensitive to changes in the operating points of the system.
In addition, the structures based on Lyapunov theory were able to deal more efficiently with the faults and the changes in the operating points of the nonlinear model of the system.
Results showed that the use of an H∞ Gain Scheduling Controller in combination with an MRAC improves the FTC performance because the controller was able to deal in an efficient manner with the faults and the changes in the operating points of the nonlinear model of the system.
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This control structure damps the active and reactive power oscillations by shifting the dominant eigenvalues to the left half-plane (LHP) in case of any changes in the operating point or droop coefficients.
Additional improvement in performance will be achieved if discrete Fourier transform (DFT) is used to quantify damping characteristic of the rotor current during changes of the operating points.
Thus, if the operating points are in the vicinity of the equilibria, then only one linear model will describe closed-loop dynamics, regardless of the rate of change of the operating points.
The parameter explained in Section 2.3 is used to change the operating points of the detectors.
These uncertainties derive from approximated and process parameters in a nonlinear system which changes as the operating point changes, a matter causing the electrical power production to reduce.
This tangential direction changes according to the operating point.
Simulation results showing the closed loop response of the system to changes in operating points, external disturbances, changes in system parameters and unmodeled dynamics are presented.
In general, this effect can change of sign with the operating point xo [ 21], but we shall not consider this scenario here.
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