Adaptive-tuning of extended Kalman filter used for small scale wind generator control

被引：12

作者：

Al-Ghossini, Hossam ^{[1
]}

Locment, Fabrice ^{[1
]}

Sechilariu, Manuela ^{[1
]}

Gagneur, Laurent ^{[2
]}

Forgez, Christophe ^{[3
]}

机构：

[1] Univ Technol Compiegne, Univ Sorbonne, EA AVE 7284, Compiegne, France

[2] TechTeam, Lyon, France

[3] Univ Technol Compiegne, Univ Sorbonne, EA LEC 1006, Compiegne, France

来源：

RENEWABLE ENERGY | 2016年 / 85卷

关键词：

Small scale wind generator; Permanent magnet synchronous machine; Extended Kalman filter; POWER TRACKING; SYSTEM; TURBINES; DESIGN; AC;

D O I：

10.1016/j.renene.2015.07.073

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

In this paper a small scale wind generator based on a permanent magnet synchronous machine (PMSM) and associated with an indirect maximum power point tracking (MPPT) algorithm is proposed. Choosing an energy conversion active structure and a sensorless PMSM, to control the system, a speed estimator is required. Facing to other methods, the extended Kalman filter (EKF) model-based estimator allows sensorless drive control in a wide speed range and estimates the rotation speed with a rapid response. The EKF parameters tuning is solved by introducing an adaptive method, i.e. adaptive-tuning EKF. This adaptive estimation approach is innovative by using a covariance matching technique. The experimental results prove that the proposed method is technically feasible with good performances within some limits. (c) 2015 Elsevier Ltd. All rights reserved.

引用

页码：1237 / 1245

页数：9

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