2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) 2020
DOI: 10.1109/iraset48871.2020.9091997
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Nonlinear sensorless control of doubly fed induction generator in wind power generation

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Cited by 1 publication
(3 citation statements)
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“…8 ( s m mean value as depicted in Figure 3. To show the robustness of the proposed adaptive sensorless controller against the aerodynamic torque and the rotor winding resistance variation the tracking performance for both the sensorless controller with [24] and without adaptation at constant wind speed ) / 9 ( s m has been compared in Figure 4. The simulation is performed with the variation of the mechanical torque and the rotor winding resistance described by: Figure 3 (c) shows a good tracking performance of the stator quadratic current.…”
Section: Simulation Resultsmentioning
confidence: 99%
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“…8 ( s m mean value as depicted in Figure 3. To show the robustness of the proposed adaptive sensorless controller against the aerodynamic torque and the rotor winding resistance variation the tracking performance for both the sensorless controller with [24] and without adaptation at constant wind speed ) / 9 ( s m has been compared in Figure 4. The simulation is performed with the variation of the mechanical torque and the rotor winding resistance described by: Figure 3 (c) shows a good tracking performance of the stator quadratic current.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…Similarly, from Figure 3(e) it can be observed that the estimated rotor resistance quickly converges to its true profiles. In Figure 4 the adaptive nonlinear sensorless controller performance is shown by the comparison of the proposed adaptive sensorless and the sensorless controller proposed in [24]. From Figures 4 (a) and 4 (b) it is noted that the stator flux and the rotor speed tracking errors sustain small perturbations caused by the unknown rotor resistance and the unknown aerodynamic torque, but they converge to zero quickly as soon as the estimates of r R , and When the actual values do not correspond to their references, the closed loop system is exposed to failure, which destroys the control objectives.…”
Section: Simulation Resultsmentioning
confidence: 99%
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