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This paper proposes an AFSMC which is designed to control the active and reactive power of the DFIG shown in Fig.
With an aim to evaluate the performances of the three controllers: SMC, ASMC and AFSMC, three types of tests have been realized: reference tracking, sensitivity to the speed variation and robustness against machine parameter variations.
It can be clear observed that the THD is reduced for AFSMC supplied by 19-level USAMI (THD = 0.67%) when compared to AFSMC (THD = 1.79%) and ASMC (THD = 1.91%) and SMC (THD = 2.06%) supplied by conventional inverter (i.e.
This figure express that the speed variation produces a slight effect on the powers curves of the system with ASMC controller, while effect is almost negligible for the system with AFSMC one.
These results show that parameters variation of the DFIG presents a clear effect on the powers curves (especially in their errors curves) and that the effect appears more significant for ASMC controller than that with AFSMC one.
In order to eliminate the chattering, we propose to use the AFSMC. Basing on all these results we conclude that robust control method as AFSMC can be a very attractive solution for devices using DFIG such as wind energy conversion systems and establish its suitability for the system drive.
Block diagram of the Adaptive Fuzzy Sliding Mode Control (AFSMC)
Table 1: The parameters of input membership functions for the AIT2FSMC and the AFSMC. Negative [m.sub.N1] [m.sub.N2] [[sigma].sub.N] AIT2FSMC -1.15 -0.35 0.6 AFSMC -1.25 -1.25 0.6 Zero [m.sub.Z1] [m.sub.Z2] [[sigma].sub.N] AIT2FSMC -0.01 0.01 0.6 AFSMC 0 0 0.6 Positive [m.sub.P1] [m.sub.P2] [[sigma].sub.N] AIT2FSMC 1.15 1.35 0.6 AFSMC 1.25 1.25 0.6
An ACS using one reaction wheel and three magnetorquers as actuators for nadir pointing with the desired quaternion that is set to (0, 0, 0, 1) is examined using AFSMC over 10 orbits.
An ACS using three reaction wheels as actuators for nadir pointing with the desired quaternion set to (0, 0, 0, 1) is examined using AFSMC over 0.1 orbits.
Compared to the PID controller, the AFSMC controller uses nearly the same gain and has much better tracking performance under these conditions.
Name Values Proportional parameters 0.03 Integral parameters 0.0001 Derivative parameters 0.11 TABLE 4: AFSMC controller parameters for air bearing testing.
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