An adaptive system based on artificial neural networks for npk fluid fertilizer application

摘要

The application process of fluid fertilizers through variable rates implemented by classical techniques with feedback and conventional equipments can be inefficient or unstable. This paper proposes an open-loop control system based on artificial neural network of the type multilayer perceptron for the identification and control of the fertilizer flow rate. The network training is made by the algorithm of Levenberg-Marquardt wih training data obtained from measurements. Preliminary results indicate a fast, stable and low cost control system for precision farming.