Adaptive robust MPPT control for wind power generation system
DOI：10.7667/PSPC171714
Key Words:wind power generation system  maximum power point tracking  adaptive control  robust control
Author NameAffiliationE-mail
MAO Jingfeng School of Electrical Engineering, Nantong University, Nantong 226019, China  
WU Bowen School of Electrical Engineering, Nantong University, Nantong 226019, China  
WU Aihua School of Electrical Engineering, Nantong University, Nantong 226019, China wahmx@163.com 
ZHANG Xudong School of Electrical Engineering, Nantong University, Nantong 226019, China  
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Abstract:In order to improve the working performance of the Maximum Power Point Tracking (MPPT) for wind power generation system, this paper proposes an Adaptive Robust Control (ARC) method to overcome uncertain problems, including unknown modeling errors and external disturbances. The ARC method is designed according to a new dynamic model of angular velocity tracking for wind power generation system based on generalized perturbation. It does not require the system model parameters and external disturbance identification. In terms of the on-line estimation of the disturbance boundary value and the nonlinear state feedback based on MPPT tracking error, the gain of the switching control is adaptively adjusted to speed up the convergence of the system. A first-order integral process is involved in the control law to further weaken the chattering of output signal amplitude, hence smooth the torque and improve the tracking accuracy during generation. In addition, the global stability of the closed-loop control system is proved by the Lyapunov approach. By simulation comparing with the conventional linear PID control and the nonlinear dynamic State Feedback Control (SFC), the results show that the proposed controller has good performance in the process of realizing MPPT and has stronger robustness and adaptability. This work is supported by National Natural Science Foundation of China (No. 61673226 and No. 51877112), Six Talents Peak Projects of Jiangsu Province (No. 2015-JY-028), and Natural Science Foundation of the Jiangsu Higher Education Institutions of China (No. 17KJA470006).
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