# Nonlinear Model Predictive Control for Doubly Fed Induction Generator with Uncertainties
## 4 Conclusions  
This paper's objective is to model and control a representative wind turbine by stabilizing the characteristics of the doubly fed induction generator (DFIG) integrated into the turbine's structure. The research is structured into three primary parts. The first part focuses on introducing a novel and accurate model for the system. To accomplish this, various research studies were reviewed to develop a comprehensive and precise model of induction generator systems. Eventually, a nonlinear model was selected for a variable-speed wind turbine. Subsequently, the conventional model predictive control (MPC) was selected as the stabilizing mechanism for the DFIG system, given its widespread use in industrial control and cost-effectiveness in implementation. Considering that the modeled induction generator system in this research is nonlinear and subject to noise and disturbances, it is evident that relying solely on conventional MPC is insufficient. Therefore, there is a need to integrate it with a suitable controller. The suboptimal performance can be attributed to two main reasons. Firstly, the wind speed input, characterized by noise and uncertainty, was not adequately filtered. Secondly, the conventional MPC's limitations in stabilizing nonlinear systems may have contributed to the observed issues. To address these challenges, a solution was proposed that involved implementing a Kalman filter to eliminate noise from the wind speed input. Additionally, a combined control strategy was introduced, integrating nonlinear MPC based on the Lyapunov function to overcome the limitations observed in the conventional MPC structure and stabilize the modeled DFIG system. This choice was made to ensure stability in the system and to deal with unwanted inputs in the modeled nonlinear system. The results demonstrated that the combined nonlinear MPC strategy based on the Lyapunov function successfully addressed the limitations of conventional MPC. Moreover, it exhibited improved performance compared to PID based control approach, marking a significant advancement in the control of the wind turbine  
Figure 12: Comparison of the response obtained from the proposed mechanism and the PID controller for the reactive power.  
system. Among the limitations of this paper is the simultaneous use of several distributed generation units in the proposed mechanism, as well as the consideration of stochastic programming to solve the problem.  
Methodology, K.M., R.W. and H.N.; Software, K.M.; Validation, X.W. and W.F.; Writing--original draft, K.M., R.W. and H.N.; Writing--review & editing, X.W. and W.F.; Supervision, W.F. All authors have read and agreed to the published version of the manuscript.  
This work was partly supported by Zhejiang Province Postdoctoral program (No. 301816) and the Research and Development Project of China Huadian Corporation LTD. (No. CHDKJ-21-01-98).  
Not applicable.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
Data Availability Statement: Data available on request due to restrictions. The data presented in this study are available on request from the corresponding author ([PERSON]).  
Authors [PERSON] and [PERSON] were employed by the company Huadian Electric Power Research Institute Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.