Research On Size Optimization And Motion Control Of Forage Sorting Delta Parallel Robo

Under the background of promoting the high-quality development of animal husbandry,forage quality is an important factor affecting the high-quality development of animal husbandry.However,due to the existence of foreign matters such as residual plastic film and harmful weeds in forage,it is necessary to remove foreign matters before fine processing of forage.Due to the variety of foreign matter and the similar characteristics of some foreign matters to forage grass,it is difficult to achieve effective impurity removal by traditional mechanical methods.In view of the characteristics of forage and foreign matter,this paper combines machine vision recognition technology to carry out effective separation of foreign matter and weeds in forage by Delta parallel robot.The main contents are as follows :1.Sorting object characteristics and parallel robot kinematics analysis.Sampling the sorting object,measuring the basic parameters,and analyzing its characteristics.According to the parameters of the sorting object,the working space of the parallel robot is designed,so as to preliminarily determine the structural size parameters of the Delta parallel robot.The forward and inverse kinematics models of parallel robot are established by geometric method and vector method,and the model is verified by Matlab programming.According to the forward kinematics solution,the parallel robot workspace is solved by Monte Carlo method.The results show that the solved workspace meets the design workspace requirements.2.The primary structure size optimization of Delta parallel robot based on performance index.According to the actual application scenarios,the mechanism size is optimized with the workspace utilization and global dexterity as indicators.The equivalent workspace is proposed for the irregular workspace,and the utilization rate of the workspace is expressed by the distance from the equivalent workspace to the actual workspace boundary.Taking the workspace utilization rate and dexterity as the optimization objective function,the genetic algorithm is used to solve the optimal structural size parameters,and the comparative analysis before and after optimization is carried out.The results show that the workspace utilization rate and dexterity of the Delta parallel mechanism are improved after optimization,which improves the motion performance of the mechanism.3.Sorting trajectory planning.In order to ensure the stability of the motion of the parallel robot tool centre position sorting process,the tool centre position motion law is optimized.The door-shaped trajectory in the commonly used conveyor belt transportation and sorting process is planned.The arc transition method is adopted at the right-angle turning point.According to the tool centre position motion,the driving angle is obtained through the inverse kinematics solution,and the key points of the path are selected for interpolation.The displacement and velocity curves of the tool centre position and drive tool centre position motions are obtained through Adams simulation,and the end path meets the requirements of smoothness.4.Dynamic response analysis and motion control of parallel robot.The servo motor model and three-loop control system were established.The single-chain system of Delta parallel robot was compared with PI speed controller and fuzzy PI speed controller.The control model was built in Simulink for simulation.According to the dynamic response results,the fuzzy PI controller had better control effect than the PI controller.The physical model of the parallel robot was established by combining Solid Works and Sim Scope.A fuzzy PID controller was built in Simulink to control the robot motion based on the physical model.The combined simulation experiment showed that the driving arm and the end had good tracking accuracy,and the tool centre position followed the expected trajectory motion.