Research on the PID Control Strategy in BP Neural Network of Terrain Detector-Milling Cutting Depth System

Xiao Feng; Hao Hu; Fan Rang Kong; Shi Qiu; Ye Sun

doi:10.4028/www.scientific.net/AMR.945-949.1573

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Automatic Weight Classifying Machine of Objects with Load Cell
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Research on the PID Control Strategy in BP Neural Network of Terrain Detector-Milling Cutting Depth System
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 945-949Research on the PID Control Strategy in BP Neural...

Research on the PID Control Strategy in BP Neural Network of Terrain Detector-Milling Cutting Depth System

Abstract:

Targeting at the nonlinear, time-varying characteristics of terrain detector-milling cutting depth electro-hydraulic servo system in soil milling collection machines, this paper proposed the PID control menthod in BP neural network of terrain detector - milling cutting depth system and designed PID controller in BP neural network and conducted simulation analysis by programming with Matlab. The results show that, when compared with conventional PID control, BP neural network compounded with PID control would enable the system better dynamic performance and follow-up characteristics, therefore, it is an effective control strategy.

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Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

1573-1578

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.945-949.1573

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Online since:

June 2014

Authors:

Xiao Feng*, Hao Hu, Fan Rang Kong, Shi Qiu, Ye Sun

Keywords:

BP Neural Network PID, Computer Simulation, Milling Cutting Depth, Terrain Detector

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