**1. Introduction**

Currently, most of the processes use a control system, which provides the necessary conditions and guarantees the correct operation of the process to obtain the final product. Additionally, there is a great variety of control systems, for example, neural networks, PID controllers, robust control, sliding modes, PLC (Programmable Logic Controllers), fuzzy controller, among others. On the other hand, the characteristics of the process must be analyzed to select a control system, for example, the cost of the control system, the software or hardware used for the implementation of the control

system, the mathematical requirements used to analyze the process, variables, types of sensors and actuators necessary to control the process, desired precision in the process, advantages and/or disadvantages of the control system, among other things. Therefore, this work shows a methodology for the implementation of a fuzzy controller in different software or hardware platforms, since a fuzzy controller does not need the mathematical model of the system, uses the experience or knowledge of a person, does not use complex mathematical equations for its implementation, and uses linguistic explanations (low, high, hot, cold, good, bad, etc.) to define process conditions and control action. Therefore, a fuzzy controller is one of the best options for controlling a process. Currently, fuzzy controllers are used in a wide variety of processes or applications; for example, modeling and simulation of the Maximum Power Point Tracking (MPPT) in photovoltaic solar energy systems [1–5], increase the accuracy in determining the degree of diabetes in a person [6, 7], identification of hot spots and analysis of the intensity of flames in pipes to prevent fires [8], improve the performance of a grid-connected wind generator system [9–11], control of the output voltage of a Boost converter [12], generate a suitable microclimate for an agricultural greenhouse [13], among other applications. On the other hand, the proposed methodology uses two control statements (IF-THEN and FOR), and the basic mathematical operations (addition, subtraction, multiplication, and division) for the design and implementation of the fuzzy controller stages. Therefore, the proposed methodology uses basic programming elements, which allows the fuzzy controller to be implemented in different software or hardware platforms. In this work, MATLAB™ and the Arduino UNO, Arduino DUE, and Nexys 4™ boards are used to show the correct operation of the proposed methodology. Also, Fuzzy Logic Toolbox™ is used to simulate and analyze the operation of the fuzzy controller. Finally, the structure of the chapter is as follows, Section 2 shows the procedure to implement the fuzzy controller in the different platforms, Section 3 shows the simulation and experimental results of the fuzzy controller, which was implemented in the different platforms, and Section 4 presents the conclusions.
