*Methodology for the Implementation of a Fuzzy Controller on Arduino, MATLAB™… DOI: http://dx.doi.org/10.5772/intechopen.109760*

used. In this case, Refs. [31, 32] was used to compare the efficiency. Arduino Mega 2560 board and the Arduino UNO board are compared. **Tables 3-5** show the results of the fuzzy controller and the MSE of the data. As can be seen, the fuzzy controller using the proposed methodology has a higher precision than the fuzzy controller taking in consideration.

On the other hand, there are research works that use a computer to implement a fuzzy controller and a hardware board as an interface to interconnect the environment (physical variables) with the computer [33, 34]. This action can increase the cost of the system and make it difficult to implement it in a process. **Table 6** shows the results of a fuzzy controller, which is implemented in MATLAB™ and used for the prediction of GSM tissue and wrinkle recovery angle of laserengraved denim [35]. Additionally, the results of the fuzzy controller implemented using the proposed methodology and the MSE are shown. As can be seen, a high degree of accuracy can be obtained in a process using the methodology proposed in this work.


#### **Table 3.**

*Test of the light intensity of an LED using a diffuse driver.*


#### **Table 4.**

*Results of the acid solution for the process using a fuzzy controller.*


**Table 5.**

*Results of the neutral solution for the process using a fuzzy controller.*


**Table 6.**

*Fuzzy controller to predict the strength values of laser-engraved denim seams.*
