# Development of Intelligent Fuzzy Controller for a Two-Axis Solar Tracking System
## 3 Intelligent Fuzzy Logic Controller  
[PERSON] [19] proposed a quantitative tool in 1965, which can be used to express an ambiguity concept, especially in the ambiguity of human language. [PERSON] carried out further research in this area. The result of their work is the fuzzy logic controller (FLC), which has now become world famous [20; 21; 22]. The main advantage of the FLC is that it can be applied in situations where the controlled body is too complex or difficult to be mathematically modeled. The design of the controller is based on a few fuzzy rules. Thus, the FLC is smart and user-friendly. Generally speaking, the operation of the FLC can be divided into four areas: (1) fuzzification; (2) decision-making logic; (3) fuzzy knowledge base; and (4) defuzzification. Fuzzification is the process that converts numerical values into grades of membership of fuzzy set members. Hence, the fuzzification block matches the input data to determine how well the condition of each rule matches that particular input. A degree of membership function for each linguistic term applies to the input variable. We apply this system in the FLC solar panel output current and define the sunlight sensor output voltage values. The fuzzy inference engine provides the input values (as shown in Figure 4). The use of fuzzy sets is defined, the membership functions are quantified, and continuous use of the triangular membership functions is made to reduce errors. Table 2 presents the variables used for fuzzy logic control. value is also known as the collection element. The ordinate represents the size of the element, also known as the degree of ownership. Among them, sunlight intensity can be divided into three states: large, medium and small; the solar panel current can be divided into three states: large, medium and small; and the output value can be divided into three states: large, medium and small. The second step of the fuzzy controller design is to determine the form of fuzzy rules and list all the relevant rules. It refers to the relationship of solar cell output current and illumination of sunshine, and past data obtained from the literature, and relevant experts, to establish the following fuzzy rule base. The control rules are evaluated by an inference mechanism and represented as a set of: _IF Sunlight sensor voltage is... and Cell current is... THEN the output will..._  
For example, Rule 1: IF sunlight sensor voltage is Small and Cell current is Small THEN the output is Low (stop). The linguistic variables used are Low (stop) and Large (start), as shown in Table 4. \begin{table}
\begin{tabular}{c c c c} \hline
**Cell Current** & **Small** & **Middle** & **Large** \\ \hline Small & Low (stop) & Large (start) & Large (start) \\ Middle & Low (stop) & Large (start) & Large (start) \\ Large & Low (stop) & Low (stop) & Low (stop) \\ \hline \end{tabular}
\end{table} 
Table 4: Fuzzy rules. Figure 5: Membership function of sunlight. Figure 6: Membership function of the output current. Figure 7: Membership function of the consequent part. The third step of the fuzzy controller design is deciding what kind of fuzzy inference engine should be used. For this system, the maximum/minimum is selected as the synthetic fuzzy inference method [23; 24; 25]. Figure 8 shows the operation of the fuzzy inference engine, which assumes that the input value (3.5 V) of sunlight intensity triggers three rules, and the one triggered by a high degree of fuzzy set intersections has been truncated (yellow area). For the first rule of fitness, the solar panel input current (0.377 A) triggered six rules. The one triggered by a high degree of fuzzy set intersections has been truncated (yellow area). The output of the fuzzy set is taken as the \(Y\)-intersection and the fuzzy set of the final will be the union of the most fuzzy sets. The whole process of computing algorithms uses Equations (1)-(3). The input variables are V (sunlight intensity), I (solar panel current), and the fitness of the front pieces (W).