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Vol. 166, Issue 3, March 2014, pp. 268-274

 

Bullet

 

Study of Tractor AMT Automatic Gear Shift Based on Artificial Neural Network
 

Liu Jiangtao, Zhang Liguo, Cui Baojian, Yi Jinggang

Mechanical & Electronic Engineering College, Agricultural University of Hebei, Bao Ding, 071001, China
Tel: +86 139 32264554, fax: 0312-7526462

E-mail: liujiangtao2003@126.com

 

Received: 24 December 2013 /Accepted: 28 February 2014 /Published: 31 March 2014

Digital Sensors and Sensor Sysstems

 

Abstract: The paper aims at the complex situation of the tractor field operation and adopts the gear shift rule of two parameters to control the six gear shift of the tractor. Using the artificial neural network chip the model number of which is ZISC036 and the computer on slice the model number of which is PIC17C42 establishes the controller of the radial basis function artificial neural network-RBFANN. Based on the optimal gear shift information emitted by the RBFANN controller, PIC17C4 emits the control command to control the hydraulic system to realize the automatic gear shift according to the predetermined rule. The sample data is simulated by MATLAB. It shows that RBFANN identification system can solve the problem of the gear recognition and the gear position can be accurately identified. The paper offers the theoretical basic for the design and study of the tractor AMT automatic gear shift.

 

Keywords: Tractor, Gear shift, RBFANN, ZISC036, PIC17C42, MATLAB

 

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