Research On Intelligent Control System Of Electric Leaf Vegetable Harvester

In the leafy vegetable production process,the harvesting operation accounts for about 40% of the entire operation,which is the most labor-intensive and time-consuming link.The domestic leaf vegetable harvesting machinery research started late,and at this stage,it is still mainly manual harvesting,which is not only inefficient but also labor intensive.Using a leaf vegetable harvester can improve field harvesting efficiency and reduce labor intensity.At present,the domestic leaf vegetable harvesting machinery has a low degree of intelligence,the road conditions are complicated during the actual operation,the friction between the wheels and the ground changes greatly,and the load of the harvester changes.As a result,the operating speed cannot be kept constant at all times,and the operator needs to constantly adjust the operating speed;On the other hand,due to changes in the terrain or the deviation of the leafy vegetable rows during the planting process,the operator needs to adjust the operation direction in real time.The above conditions will have a direct impact on the harvest efficiency and quality.Therefore,there is an urgent need to study the two aspects of operation speed and automatic line control.This paper studies the intelligent control system of the electric leaf vegetable harvester in view of the above problems.The main research work is as follows:(1)Intelligent control technology for operating speed.The intelligent control technology of job speed based on online NQL-PID is proposed.By analyzing the control process of the walking drive system of the electric leaf vegetable harvester,the mathematical model of the vehicle's drive motor is established,and the transfer function of the input voltage of the brushless DC motor to the output speed and the transfer function of the drive motor to the wheel are determined on this basis.PID,fuzzy PID and online NQL-PID control strategies were simulated.Six working conditions including constant load start,variable load start,constant speed sudden load increase,uniform speed slow load increase,uniform speed sudden load decrease and uniformspeed slow load decrease were simulated.The simulation results show that the online NQL-PID control strategy can improve the real-time and stability of the system response and improve the performance of the system.(2)Automatic intelligent control technology.The automatic regulation technology based on fuzzy PID is proposed.A mechanical alignment detection mechanism was designed,and a mathematical model of the steering mechanism was established.Based on this,a corresponding fuzzy PID control strategy was established,and a lateral fixed value offset was generated for the leaf vegetable row during the operation,and a horizontal direction was generated for the leaf vegetable row during the operation.Two kinds of situations,such as fluctuation offset,were simulated.The simulation results show that the established control model can realize the automatic alignment function of the harvester and improve the automation degree of the harvester.(3)Software and hardware design of the control system.By analyzing the working principle and operation process of the electric leaf vegetable harvester,the overall plan of the control system is proposed,the relevant hardware selection is carried out,the design of the human-computer interaction interface is completed,the online NQL-PID speed control algorithm is compiled,and the automatic fuzzy PID Control algorithm and cutter,conveyor motor control program,developed a prototype of intelligent control system of electric leaf vegetable harvester.(4)Control system performance test.Taking the test frame as an object,a control system is installed to test the intelligent control system of operating speed,and the test is conducted under three conditions: constant load start,constant speed sudden load increase,and constant speed sudden load decrease.The results show that the online NQL-PID control strategy can reach the set speed faster during the constant load startup,and its adjustment time is reduced by 27.8% compared to fuzzy PID and 35% compared to PID,and the load is increased at a constant speed.3.The speed can be adjusted to the set speed more quickly during the constant speed sudden load reduction;when the constant speed sudden load increase,the online NQL-PID control strategy reduces themaximum speed deviation by 20.23% compared to the fuzzy PID,and reduces the PID by 34.77%,Compared with fuzzy PID,the transition process time is reduced by 21.42%and PID by 31.25%;when the load is suddenly reduced at a constant speed,the online NQL-PID control strategy reduces the maximum speed deviation of fuzzy PID by21.06%,compared to The PID is reduced by 36.48%,and the transition time is reduced by 23.77% compared to fuzzy PID and 33.3% compared to PID.The performance test of the automatic alignment control system.When the deviation of the leaf vegetable line is detected,the control system can quickly drive the steering wheel to deflect to adjust the working direction.The maximum deflection angle is 14.9 °.The body adjustment is completed after 2s,and then Enter the fine-tuning state to achieve the expected effect;start and stop action and speed control test on the cutting blade and conveyor drive motor.The test results show that the two sets of DC brushless system have good performance,stable operation,the absolute error is 2.1r/min,and the speed variance The maximum is 1.05 and the minimum is 0.65.