Design And Performance Test Of Camellia Fruit Harvester Walking Control System

When camellia oleifera fruit harvester walking in the complex road environment of the woodland,whether it can quickly,safely and accurately reach the designated position for picking operations will affect the efficiency of the entire picking process,among which the performance of the chassis walking control system of Camellia oleifera fruit harvester is one of the keys.Camellia fruit harvester is driving between the forests.The road conditions are very complicated.Not only are the ground uneven,but also the hard objects with different heights of the ground,such as stone or residual tree root tree pockets,etc.As a result,when the camellia fruit harvester is driving in a straight line,due to the uneven force on both sides of the crawler,the driving direction is deflected at a large angle.At present,there are few studies on the control of harvesters driving in a straight line in complex woodland.In this study,the hydraulic crawler chassis of Camellia fruit harvester is taken as the research object to study the linear driving control of Camellia fruit harvester in the forest.The main research work carried out in this thesis is as follows:(1)According to the working principle diagram of the hydraulic system,the state space equation of the hydraulic walking control system is built up,and the speed of a single hydraulic motor is controlled by using PID control technology.In order to ensure that the harvester of the camellia fruit picking machine moved between the two positions,it can reach the position in the shortest time when it is disturbed by road obstacles,an real-time adjustment of the PID parameter to the fuzzy neural network PID controller is raised which based on an cross-coupling synchronization of straight walking control strategy.Finally,the initial parameters of the neural network are optimized by using the Golden Jackal Optimization Algorithm.(2)With STM32 microcontroller as the main control unit,the lower computer containing power module,speed sensor,attitude sensor and wireless communication module was designed,and the printed circuit board is designed.(3)Based on the Android mobile phone platform,the upper machine is developed with Android Studio which can communicate with lower machine through wireless connection.(4)The Simulink simulation module was built to simulate the control effect and test it on the real machine.The experimental results show that the average heading deflection angle of the Camellia oleifera fruit harvester in a synchronous straight line is 7.8° by using the improved fuzzy neural network PID control,which is 32.2%lower than that of the PID control.So the improved fuzzy neural network PID control can meet the requirements of the Camellia oleifera fruit harvester driving in the forest better.By applying the improved fuzzy neural network PID control to the left and right hydraulic motors of Camellia fruit harvester,the heading declination angle of the harvester can be effectively reduced,and the conclusion with practical engineering significance is obtained,which provides a certain reference for the intelligent operation of Camellia oleifera fruit picker in the forest.