ABSTRACT:The demand of the agricultural sector for more operationally efficient machines and implements motivated the development of alternatives for driving of this equipment. Aiming an electrical supply to apply in agricultural implements, this study proposes a system that uses the tractor power take off to activate a synchronous generator, using a fuzzy logic controller designed to regulate the generated voltage level. Different control architectures were tested and evaluated by simulations. In the initial stage were evaluated fuzzy PI, fuzzy PD and fuzzy PID controllers of multiple inputs and single output (MISO) and the error of the generated voltage as state variable. Subsequently, it was evaluated a fuzzy PI controller of single input and multiple outputs (SIMO) with a modified rule base for the system. In the final stage, the angular drive speed was included as state variable of the controller. The behavior of each architecture was analyzed by means of performance indexes. The results show that among the tested controllers, the modified fuzzy PI SIMO presented the best performance values while maintaining the operating variables within the established limits.

So that the levels of water stress are not harmful to the development of the crop and affect its productivity, its detection and monitoring are necessary, and it can occur in different ways. One of them is through the Crop Water Stress Index (CWSI). This index quantifies water stress through the normalization of leaf temperature between the maximum and minimum plant temperatures as a function of evaporation conditions. The responses of a low-cost infrared (IR) sensor were crossed with image processing through segmentation by the Excess Green model to develop a water stress detection system using CWSI. A soil/plant temperature map was generated through a point-to-point scan of the IR sensor. And when it overlaid with a segmented image of the experimental area, only points identified as plants had their temperature values maintained. The Non-Water-Stressed Baseline (NWSB) equation was parameterized for the same conditions of the experiment and external environmental. The experimental area was divided into three different treatments, maintained under stable water conditions throughout the experiment and the system was able to identify stably different stress values between treatments. Although the relationship between crop and environment affected the results, this work showed that using an irrigation system based on CWSI is possible.

Precision Irrigation (PI) is a promising technique for monitoring and controlling water use that allows for meeting crop water requirements based on site-specific data. However, implementing the PI needs precise data on water evapotranspiration. The detection and monitoring of crop water stress can be achieved by several methods, one of the most interesting being the use of infra-red (IR) thermometry combined with the estimate of the Crop Water Stress Index (CWSI). However, conventional IR equipment is expensive, so the objective of this paper is to present the development of a new low-cost water stress detection system using TL indices obtained by crossing the responses of infrared sensors with image processing. The results demonstrated that it is possible to use low-cost IR sensors with a directional Field of Vision (FoV) to measure plant temperature, generate thermal maps, and identify water stress conditions. The Leaf Temperature Maps, generated by the IR sensor readings of the plant segmentation in the RGB image, were validated by thermal images. Furthermore, the estimated CWSI is consistent with the literature results.

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