Research On Tracking Control Technology Of Agricultural Machinery Automatic Driving Based On Multi-data Fusion

In recent years,the National Central Government Document No.1 focused on agriculture,rural areas and farmers,and emphasized the development of precision agriculture.Automated driving control technology is an important part of modern agricultural intelligence.The automatic driving system of agricultural machinery has complexity and uncertainty in the operating environment.Controlling the automatic driving of agricultural machinery accurately and quickly is an important requirement for precision agriculture.This article takes agricultural machinery as the research object,obtains the position and attitude of agricultural machinery from multiple data fusion,linear path tracking based on pure tracking model,fuzzy immune PID algorithm to control hydraulic steering of agricultural machinery,and realizes the research on key technologies of automatic driving control of agricultural machinery.The smart car model is tested experimentally.In this paper,aiming at the shortcomings of BDS misalignment and INS single navigation error in the case of environmental interference,this paper proposes a bee colony algorithm to optimize the BP neural network-assisted Kalman filtering algorithm for integrated navigation based on the position and speed difference between the BDS/INS.Accurately locate the position and speed information of agricultural machinery.When BDS is effective,BDS/INS integrated navigation combined with Kalman filtering,corrects the position and speed deviation of INS,and BP neural network is used for training mode.When the BDS is out of order,the BP neural network is converted into a prediction mode,which replaces the BDS to correct the feedback of the INS and outputs accurate position information.At the same time,this paper improves the search method and selection probability of artificial bee colonies,and uses an improved bee colony algorithm to optimize the BP neural network to achieve accurate positioning of agricultural machinery's position and speed.In this paper,a pure tracking algorithm is used to track the straight line of agricultural machinery,and the nonlinear relationship between forward looking distance,lateral position difference and heading deviation is obtained.The paper adopts the idea of fuzzy control and combines the lateral deviation value and the heading deviation value to obtain the deviation angle value of the desired path between the agricultural machine and the target.At the same time,this paper proposes an immune fuzzy PID algorithm,which combines the fuzzy PID algorithm with immune theory.The fuzzy algorithm optimizes the PID IK ?DK and the immune theory optimizes the PID PK.It is applied to hydraulic steering technology to implement agricultural machinery path control.Through simulation experiments,it is proved that the immune fuzzy PID algorithm has fast response speed,short adjustment time and good stabilization effect.Finally,this paper builds an experimental platform for automatic driving of agricultural machinery,designs the system's core control module,BDS/INS high-precision combined positioning module and steering circuit,builds an intelligent model car,and experimentally verifies the precise positioning and linear path tracking control of automatic driving.