# Adaptive Pitch Control of Variable-Pitch PMSG Based Wind Turbine
## 5 Conclusions  
This paper has developed a nonlinear adaptive pitch controller for the PMSG-WT to limit the extracted power from time-varying wind in Region 3. In the proposed NAC, all time-varying and unknown dynamics of the PMSG-WT, e.g., nonlinearities, parameter uncertainties and disturbances, are included by defined perturbation terms, which are estimated by designed POs and SPO. The estimated perturbations are used to compensate the real perturbations for fully linearizing the PMSG-WT system. The proposed NAC has overcome the drawbacks of the FLC relying on the full system states and detailed nonlinear system model, the shortcoming of the VC designed based on a specific operating point, and the disadvantages of the GSPI scheduling PI gains frequently under time-varying wind speeds. Simulation studies are carried out for the comparison of the control performance achieved by the VC, FLC, GSPI and NAC under different scenarios. Compared with the FLC, GSPI and VC, the proposed NAC provides the best performance under different scenarios and achieves highest robustness against field flux variation. Wind speed sensorless control approach will be focused on in further work. The effective wind speed cannot be directly measured by anemometers, but it can be estimated through employing the WT itself as a wind speed measurement device [8].  
Conceptualization, J.C. and B.Y.; validation, J.C. and B.Y.; investigation, J.C. and W.D.; methodology, T.Y. and N.A.; writing--original draft preparation, J.C.; writing--review and editing, W.D. and B.Y.; visualization, H.S. and L.C.; supervision, H.S. and L.C.; project administration, J.C., B.Y. and T.Y.; funding acquisition, J.C., B.Y. and T.Y.  
This research was funded by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 19 KJB470036), National Natural Science Foundation of China grant number (Grant Nos. 51667010, 51777078), the Fundamental Research Funds for the Central Universities (Grant No. D2172920), the Key Projects of Basic Research and Applied Basic Research in Universities of Guangdong Province (Grant No. 2018 KZDXM001), and the Science and Technology Projects of China Southern Power Grid (Grant No. GDKJXM20172831).  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Simulation Scenarios**} & \multirow{2}{*}{**Variables**} & \multicolumn{4}{c}{**Controllers**} \\ \cline{3-5}  & & **VC** & ** FLC** & **NAC** \\ \hline \multirow{3}{*}{Ramp wind speed} & \(IAE_{\omega_{m}}(\text{rad})\) & 0.817 & 0.1555 & \(1.397\times 10^{-5}\) \\  & \(IAE_{i_{4}}(\text{A}\cdot\text{s})\) & \(9.603\times 10^{-15}\) & \(1.025\times 10^{-13}\) & \(3.076\times 10^{-5}\) \\  & \(IAE_{i_{4}}(\text{A}\cdot\text{s})\) & \(8.634\times 10^{-13}\) & \(6.972\times 10^{-12}\) & \(2.752\times 10^{-3}\) \\ \hline \multirow{3}{*}{Random wind speed} & \(IAE_{\omega_{m}}(\text{rad})\) & 1.369 & 1.273 & \(1.514\times 10^{-3}\) \\  & \(IAE_{i_{4}}(\text{A}\cdot\text{s})\) & \(9.98\times 10^{-15}\) & \(1.075\times 10^{-13}\) & \(6.75\times 10^{-3}\) \\  & \(IAE_{i_{4}}(\text{A}\cdot\text{s})\) & \(9.598\times 10^{-13}\) & \(7.154\times 10^{-12}\) & 0.6171 \\ \hline \multirow{3}{*}{Field flux variation} & \(IAE_{\omega_{m}}(\text{rad})\) & 0.0695 & 0.207 & \(2.995\times 10^{-6}\) \\  & \(IAE_{i_{4}}(\text{A}\cdot\text{s})\) & \(9.526\times 10^{-15}\) & \(1.24\times 10^{-13}\) & \(1.852\times 10^{-5}\) \\ \cline{1-1}  & \(IAE_{i_{4}}(\text{A}\cdot\text{s})\) & 67.78 & 1957 & 0.04528 \\ \hline \hline \end{tabular}
\end{table}
Table 3: IAE indices of different controllers in different scenarios.