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The increasing global energy demand has led the world to exploit Solar Energy as an alternate energy source thanks to its availability, inexhaustible nature and cleanness. (Green, 2002; Xu, Moulema, Ge, Song, & Yu, 2016; Taylor, Koutroulis, &laabjerg, 2015).
To date, the grid-connected Photovoltaic (PV) systems are tremendously exploited in online applications. Generally, the compatibility with the grid utility is a challenging issue that numerous papers in the literature are trying to solve in order to enhance the efficiency of the grid-connected PV Generator (PVG) (Raducu, 2008; Badis, Boujmil, &Mansouri, 2019).
The boosting and the inverting stages usually take place in the power conversion system. However, this system is known to suffer from the irregular behavior of the PV system. The unpredictable internal and external changes make the operating point vary due to the control unit and the parametric errors. In connection with these problems, the use of robust control laws is crucial for ensuring the stabilization and the good tracking. Interestingly, many researchers are working on the conversion chain of grid-connected PV systems (Alajmi, Ahmed, Finney, & Williams, 2011; Bo, Wuhua, Yi, & Xiangning, 2010; Kottas, Boutalis, & Karlis, 2006; Menniti, Pinnarelli, & Brusco, 2011).
Hence, the proposed grid-connected PV system has to guarantee the following threefold evaluations:
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Making the PV array operate at its Maximum Power Point (MPP) at all times.
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Tight control of the DC link voltage.
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Inject a harmonic free output power to the grid by using the DC/AC inverter.
In order to achieve those goals, there has been a considerable progress made in optimization techniques. Typically, a current controller with fast dynamic response and high performance is required to satisfy the standard specifications. Accordingly, the fundamental goals are to minimize the steady-state tracking error and to ensure that the system is stable and robust under varying system parameters, voltage dips, and uncertainties.
Several control approaches have been developed for grid-connected PV systems. Even though these control strategies can achieve the same targets, they differ quite considerably in performance. The Proportiaonal Integral Derivative (PID) controller has been significantly explored in many applications over the past decades since it performs well in linear systems as compared to many new advanced control strategies, namely model predictive control (Hu, Zhu, & Dorrell, 2015), fuzzy PI control (Thumu, & Harinadha Reddy, 2019; Ganesan, Vasant, Sanghvi, Thomas, & Litvinchev, 2020), neural control (Boumaaraf, Talha, & Bouhal, 2015), etc (Singh, & Padhy, 2017). However, these techniques vary in terms of complexity, speed and precision under special conditions such as varying parameters, the PID controller becomes unreliable.