Future of generation depends on the renewable energy resources due to lack of fuel and the problems of emissions. Photovoltaic (PV) system is a promising type of renewable energy resources. Non uniformity of irradiance, temperature variation, and partial shading conditions are the main disturbances associated with PV systems. Most of literatures focus on enhancing the PV performance and to achieve Maximum Power Point Tracing (MPPT) based on offline Optimization techniques. These techniques suffer from complicated mathematical burden, long computing time, and should be repeated for any change in the operating conditions/system parameters. This paper proposed a hybrid adaptive controller to improve the system performances under several disturbances, as well as to stabilize the operation of the MPPT. Thus, the proposed controller affords tight and accurate MPPT. The gains of the proposed controller are updated automatically with the variation in the operating conditions. The initialization of the proposed a hybrid adaptive controller is carried out utilizing the Sine-Cosine Algorithm (SCA). Finally, the proposed system is evaluated through comparison with one of the newly presented techniques that achieve accurate MPPT.

由于缺乏燃料和排放问题，发电的未来取决于可再生能源。光伏（PV）系统是一种很有前途的可再生能源。辐照度不均匀、温度变化和部分阴影条件是与光伏系统相关的主要干扰。大多数文献侧重于基于离线优化技术提高光伏性能和实现最大功率点跟踪（MPPT）。这些技术具有复杂的数学负担、较长的计算时间，并且应对操作条件/系统参数的任何变化重复进行。本文提出了一种混合自适应控制器，以在多种扰动下提高系统性能，并稳定 MPPT 的运行。因此，建议的控制器提供严格和准确的 MPPT。建议控制器的增益会随着操作条件的变化而自动更新。所提出的混合自适应控制器的初始化是利用正余弦算法 (SCA) 进行的。最后，通过与实现准确 MPPT 的新提出的技术之一进行比较来评估所提出的系统。