Maximum power point tracking of permanent magnetic synchronous generator using per-turbation observer based sliding-mode control

被引:0
|
作者
Yang B. [1 ]
Shu H.-C. [1 ]
Zhu D.-N. [1 ]
Yu T. [2 ]
机构
[1] Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming, 650500, Yunnan
[2] College of Electric Power, South China University of Technology, Guangzhou, 510640, Guangdong
基金
中国国家自然科学基金;
关键词
Maximum power point tracking; Permanent magnetic synchronous generator; Perturbation observer; Sliding-mode control;
D O I
10.7641/CTA.2018.70905
中图分类号
学科分类号
摘要
This paper designs a perturbation observer based sliding-mode control (POSMC) of permanent magnetic synchronous generator (PMSG) for maximum power point tracking (MPPT). Firstly, the generator nonlinearities, parameter uncertainties, unmodelled dynamics, stochastic wind speed are all aggregated into a perturbation, which is estimated online by a perturbation observer. Then, sliding-mode control (SMC) is employed to fully compensate the perturbation estimate, such that a globally consistent control performance under various operation conditions and significant robustness against different uncertainties can be achieved. Meanwhile, POSMC adopts the perturbation estimate to replace the upper bound of perturbation used in SMC, thus POSMC can effectively resolve the over-conservativeness of SMC hence more proper control costs could be resulted in. Lastly, POSMC is easy to be implemented as it does not require an accurate PMSG model while only the measurement of d-axis current and mechanical rotation speed is needed. Three cases are carried out, including step change of wind speed, stochastic wind speed, and generator parameter uncertainties. Simulation results demonstrate that POSMC can extract the optimal wind power and provide the greatest robustness in various operation conditions compared to that of vector control (VC) and SMC. At last, dSpace based hardware-in-loop (HIL) test validates the implementation feasibility of the proposed approach. © 2019, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
引用
收藏
页码:207 / 219
页数:12
相关论文
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