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Electronic spray controllers are designed to minimize the variation in rates of inputs applied in the field. Are part of a system of control and allow the compensation of speed variation of spray displacement during operation. There are several types of spray controllers electronic available on the market. So, a way to select the most efficient under the same conditions, i.e. in a same system of control, is quantifying the response time of system for each specific controller. The aim of this study was estimate such response times. In order to simulate the experiment in the field, a workbench was designed in Laboratory of Application Technology, consisting of: electronic spraying controller, speed simulator, data acquisition base and hydraulic system. Response times were estimated by nonlinear regression models, resulting from the sum of linear regressions weighted by cumulative distribution functions. The models used were Logistics and Gompertz, resulting from a weighted sum of two linear regression with weights given by cumulative distribution function Logistic and Gumbel, respectively. Reparametrizations have been proposed for inclusion the response time of system of control as a parameter of the models, in order to improve the interpretation and statistical inference.
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