## 1 Introduction  
Greenhouses are systems that protect crops from factors that can cause them damage. They consist of a closed structure with a cover of translucent material. The objective of these is to maintain an independent climate inside, improving the growth conditions for increasing quality and quantity of products. These systems can produce in a certain place without any restriction of agroclimatic conditions. However, they must be designed according to the environmental conditions of the place where they will be installed. Control of the microclimate is necessary for optimal development of the plant since it represents 90% of the yield of crop production, where the equipment, shape, and elements of the greenhouse will depend on how different the outdoor climate is from requirements of the plant [1; 2; 3; 4]. When speaking of the greenhouse climate, reference is made to the environmental conditions that the plants require to be in good condition [5]. The greenhouse microclimate is complex, multiparametric, non-linear and depends on a set of external and internal factors. External factors include meteorological factors such as ambient temperature and humidity, the intensity of solar radiation, wind direction, and speed among others. Internal factors are crops, greenhouse dimensions, greenhouse components and elements such as heating, fogging and ventilation systems, soil types, etc. [6]. There are two different approaches to describe the greenhouse climate: one is based on energy and mass flow equations that describe the process [7; 8; 9; 10; 11; 12; 13] and the other consists of the analysis of input and output data of the process using a system identification approach [2; 14; 15; 16; 17; 18]. However, even with these approaches, it is difficult to fully account for all of these factors. In this sense, it is desirable to solve the microclimate problem based on modern methods of non-linear and adaptive systems [19]. It is important to describe the greenhouse climate to design a good control system since it is a way of manipulating the variables that affect its behavior [20]. The greenhouse climate control provides a favorable environment for cultivation and this achieves predetermined and optimal results. Nowadays, several control techniques and strategies, such as predictive control [16; 21; 22; 23], adaptive control [24; 25; 26; 27], non-linear feedback control [28; 29], fuzzy logic (FL) control [30; 31], robust control [15; 32; 33; 34] and optimal control [35; 36; 37] have been proposed for the control of the greenhouse environment. However, for the environmental control of greenhouses, conventional proportional, integral and derivative controllers (PID) are mainly developed due to their flexibility, architecture and good performance [38]. Another topic of interest derived from the production of greenhouse crops is energetic consumption, in which solar energy is presented as a viable substitute for traditional sources (fuel and electricity). Solar energy is better than traditional sources because fuels are not renewable and represent high cost [39]. Traditional energy sources can be replaced with other sustainable energies, such as solar energy, wind energy [40], biomass [41; 42; 43], geothermal energy [44; 45; 46], degeneration systems [47; 48], among others. However, use of solar photovoltaic cells or solar thermal energy in greenhouses are more widely used and can commonly be combined with other sustainable energy systems [49]. Solar greenhouses provide a controlled system cultivation, the most focus is to reduce heating energy requirements, i.e., the heating requirement is largely derived from the sun [39]. Furthermore, solar energy represents a primary element in the heating of greenhouses and makes it possible to minimize production costs [50].