Modeling, Simulation, and Setting the Control Parameters for Automation of Irrigation System Using PID and ANN methods

Abstract

Irrigation systems have been demanding automation of the system for getting faster and more precise manner of agriculture which will be enhanced the productivity rate and reduced the processing time and labor cost. During automation, irrigating the large areas of plants is a difficult job. To overcome such problems, irrigation scheduling techniques can be applied to monitor the soil and crop conditions. Irrigation scheduling plays a vital role when irrigating the land and how much water is to be applied. This improves the irrigation system as well as reduces the irrigation cost and increases crop yield. For this purpose, modeling, simulation, and setting of the control parameters for the automation of the irrigation system are carried out using Proportional-Integral-Derivative (PID). Further, to improve the performance of the control system, Artificial Neural Network (ANN) based intelligent control system is applied for effective irrigation scheduling where evapotranspiration, ecological conditions, type of crop, and the amount of water is is estimated for irrigation The model is simulated using MATLAB software, and it is found that ANN-based intelligent control systems can provide a better solution for saving the resources and can also provide optimized results to different types of agriculture cultivation.