Maximum power point tracking (MPPT) is used to utilize intermittent solar power fully in the photovoltaic (PV) systems. Tracking the MPP fast, and accurately with changes in the solar irradiance, and the temperature is the goal of MPPT techniques. In this paper, a hybrid MPPT method based on iterative learning control (ILC), and perturb, and observe (P&O) algorithm is proposed. ILC can deal with the periodic variations to eliminate the steady-state oscillations, and errors, when the operation point is close to the MPP or a small irradiance variation occurs. In the proposed hybrid MPPT technique, a high frequency power P&O method without deadtime is used to improve the dynamic response when the irradiance changes rapidly. This paper presents the theoretical background of the hybrid MPPT algorithm, design, and stability analysis. Simulation, and hardware validation results substantiate the effectiveness of the proposed method.

中文翻译：

---

基于迭代学习控制和扰动观察法的混合最大功率点跟踪方法

最大功率点跟踪（MPPT）用于在光伏（PV）系统中充分利用间歇性太阳能。快速，准确地跟踪MPP（随着太阳辐照度和温度的变化）是MPPT技术的目标。提出了一种基于迭代学习控制（ILC），扰动和观察（P＆O）算法的混合MPPT方法。当工作点接近MPP或发生小的辐照度变化时，ILC可以处理周期性变化以消除稳态振荡和误差。在提出的混合MPPT技术中，使用无死区时间的高频功率P＆O方法来改善辐照度快速变化时的动态响应。本文介绍了混合MPPT算法的理论背景，设计和稳定性分析。模拟，