Research on BP Neural Network PID Orchard Transporter Leveling System
Aiming at the problem that the slope of the hilly orchard area is large and the fruit box is prone to overturning during the transportation of the fruit box,according to the different inclination state of the transport vehicle during the driving process,a PID fruit box leveling control scheme based on the BP neural network is designed,and the simulation analysis is carried out.It shows that it is an ideal state when the inclination angle drops below 2°.When the road disturbance is 25°,20°,15°,the time re-quired for the BP neural network PID to reach the ideal state is 3.3s,2.8s,2.4s,respectively.Compared with the classic PID con-troller,the efficiency of the control scheme is increased by 13.1%,22.2%,and 31.4% when it reaches the ideal state.The peak values were optimized by 19.43%,14.68%,and20.42% .The test results show that on a slope of 20°,the error is 1.1°when reach-ing the steady state,and it takes 5.5s;on a slope of 25°,the error is 1.8°when reaching the steady state,and it takes 6.4s.The simulation and test results show that the PID fruit box leveling control method based on BP neural network proposed in this paper has good control effect and stability.It has guiding significance for the actual production process.
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