Coordination Control And Optimization For Field Intelligent Irrigation System

Irrigation process is a significant link in the field of agriculture.Currently,the main question of the irrigation system is the contradiction between the straightforward agricultural irrigation method and the growing demand of precise agriculture irrigation.Compared with precise agriculture irrigation,the rough irrigation’s style considers less details in the irrigation control process,which is mainly decided by human’s experiences,and results in more water resource’s waste and lower availability.The precise irrigation’s style requires a control algorithm which is aiming to realize a better performance against the time-delay character brought by the physics distribution of irrigation region.Meanwhile,the irrigation network’s topology optimization and water resource allocation optimization is also being considered in actual application scenarios.In the context of irrigation system,the irrigation process control as well as irrigation network’s topology and water resource allocation optimizations have been accomplished by this paper in micro and macro views respectively:(1)Establishment of the irrigation process model.The process control model transforms from a partial differential equation.Then,a predictive control method deploys to fit for the time-delay character which is obtained by analysis of the irrigation process control model.Meanwhile,control nonlinear functions inspired by the hormone regulation mechanism are proposed and the actual effect influenced by its parameters in control process has been discussed.In the end,the NUPC’s performance and effect has been verified in specific condition by changing the set point and parameters of control model respectively.(2)A coordination control algorithm has been achieved according to the Hypothalamus-Pancreas islet axis’ s regulation and control mechanism.The first level controller is designed by the mechanism of hypothalamic glucose control which is aiming to get the second-level controller’s set point.Then,the second level controller inspired by coordination mechanism between alpha cells and beta cells of islet is proposed which uses two types of nonlinear functions to simulate the antagonism relationship to get the final control output.Last,the HPCOC’s performance and effect has been verified in specific condition by changing the set point and parameters of control model respectively.(3)Decomposition of the irrigation network optimization into double-layer optimization.The first layer is topology optimization as well as the second layer is water resource optimization.In the first-layer’s optimization,the main work is to improve the immune optimization algorithm by changing the variation process to get a better local-searching capability according to the network’s distribution status.Thus,the first-layer’s optimization can reach an optimal solution of irrigation network’s topology.Moreover,in consideration of the water resource’s volume and distribution,the second-layer’s optimization uses the penalty function to solve the no-solution or wrong-solution problem caused by deficit irrigation.This double-layer irrigation optimization algorithm has a higher time efficiency compared with particle swarm optimization in the condition of the irrigation network contains large quantities of irrigation nodes.At the end of this paper,the conclusion has been summarized according to the research course and the further research has also been discussed and suggested.