Design And Experimental Study Of Model Predictive Cutting Depth Control System Fou Sugarcane Harvester

Due to the influence of topography and sugarcane harvesting conditions,how to measure the depth of the cutter and keep it at a suitable depth is difficult-for the sugarcane harvester to cut into the soil.Research shows,the depth of the cutter can be reflected by the load pressure of the cutting system,and based on this,the automatic control of cutting depth of cane harvester can be realized.However,conventional closed-loop control systems have disadvantages such as poor adaptability and low reliability.Therefore,it is of great significance to develop a model predictive control system of sugarcane harvester with high adaptability and reliability for mechanization promotion of sugarcane harvesting.The research content of this paper is mainly divided into the following aspects:First of all,this paper obtains the load pressure of the cutting system under the orthogonal test of the load pressure of the cutting system with different soil.Based on the test results as the training samples,the BP neural network model has been build to predict the load pressure of the cutting system,and to provide the reference pressure predicted value for the predictive control system.At the same time,the influence of depth and sugarcane on the load pressure was explored through the single factor test,and all the work we did above provide data basis for determining the upper and lower limits of the predicted pressure of predictive control system,And the identification of sugarcane signal.Secondly,combined with the basic principle of MPC and the closed-loop control system of the grave cut of sugarcane harvester,the project design of the MPC system of the grave cut of sugarcane harvester was completed,and the system’s stability and theoretical error were analyzed.Taking KINGVIEW as the OPC server,the data exchange between the slave computer PLC and the load pressure prediction model,the output of historical data of earth cutting and the design of man-machine interface are realized.The historical data of soil cutting can provide the data base for the knowledge base system of load pressure,and the prediction model can be optimized.Finally,the MPC system of sugarcane harvester is applied to the experimental cutting platform of the research group.The experimental results show that the predictive control system of sugarcane harvester in this paper can do a precise prediction of the load pressure of different sugarcane cutting systems,with an average relative error of 3.5%and a maximum error of 8.5%.The predicted results were used as the setting input of the closed-loop control system to realize the fixed-depth control of the cutter,and the maximum control error of the system was obtained to be about 6 mm.At the same time,the sugarcane signal could be effectively recognized to meet the requirements of actual sugarcane production and harvest.The main research contents of this paper can be divided into three aspects:load pressure test and prediction of different earth cutting systems,design of predictive control system for depth of grave cut of sugarcane harvester and test verification of predictive control system.It has certain reference significance for the practical application of the sugarcane harvester.