## 1 Introduction  
The entire world lives in a great crisis of energy and environment. This fact behooves many researchers to look for efficient and clean energy sources. Producing clean energy can reduce the pollution caused by carbon dioxide emissions (CO\({}_{2}\)). Therefore, several countries are installing solar and wind power plants to decrease these CO\({}_{2}\) emissions [1; 2]. One drawback of these energies is their dependency on weather conditions. Solar energy depends on the sun, and the wind tends to blow intermittently. Furthermore, storing surplus energy produced during times of abundance is a hard task. Fuel cells are thus one of the most important alternative sources of clean renewable energy. Moreover, due to their effectiveness and reliability, fuel cells have become one of the most promising power generators. They can provide a continuous power supply throughout all seasons as long as fuel is provided. The most preferable fuel is hydrogen. Hydrogen is a clean renewable energy source. A PEM fuel cell (PEMFC) is a fuel cell that combines hydrogen and oxygen to produce energy. It is characterized by several advantages including a quiet operation, robustness and high efficiency, and produced energy with zero levels of pollutant gases, which is why it is touted as environmentally friendly [3; 4]. In many applications, fuel cell generators are used in conjunction with power convertersthat provide an efficient power conversion from the cell stack to the load and that offer a regulated output voltage [5]. Since the PEMFC generates a low output voltage, a high step-up power converter is used to boost and regulate the fuel cell voltage in order to make the PEMFCs operate at the optimal power point as well as providing an applicable direct current (DC) power source. On the other hand, the PEMFC output characteristics are influenced by changes in several parameters, such as the cell temperature, the oxygen and hydrogen partial pressure, and the load demands [6]. Therefore, an MPPT algorithm must be established for optimal and proper operation. In the literature, a great number of classical MPPT methods have been reported [7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34]. However, the most commonly used are fractional short or open-circuit (FSC, FOC) [7; 8], perturb and observe (P&O) [9; 10; 11], voltage- and current-based MPPT [12], incremental conductance (Inc-Cond) [13; 14; 15], extremum seeking control (ESC) [16; 17; 18; 19], sliding mode control (SMC) [20; 21; 22; 23], current sweep (CS) [24], and fuzzy logic control (FLC) [25; 26; 27; 28; 29; 30]. Smart and advanced computing techniques such as eagle strategy control (ESC), particle swarm optimization (PSO), neural network control (NNC), and genetic algorithms (GAs) have also been commonly used in the last few years [35; 36; 37; 38; 39; 40; 41; 42]. Each method of these existing algorithms is characterized by its complexity in hardware implementation, convergence speed, the sensors required, the sensed parameters, and the cost. Despite the simplicity of the fractional open-circuit voltage and current, shown in [7; 8], a low efficiency and accuracy remain their main drawbacks. The P&O and Inc-Cond techniques are widely used as conventional algorithms with certain features and drawbacks. The P&O algorithm has the drawback of oscillations around the operating power point, which yields a loss of a considerable amount of power [10]. Moreover, the response of the P&O technique is slow-moving under rapid changes in operating conditions. Many other algorithms such as the variable step-size incremental resistance algorithm (VSIR) and the gradient descent algorithm (GRD) may overcome the drawbacks of these well known P&O and Inc-Cond methods [13; 14; 43]. Several advantages of ripple correlation control (RCC) over P&O are discussed in [44; 45; 46]. According to [47], despite its hardware implementation complexity, the sliding mode control technique shows high accuracy compared with conventional methods.