The control strategy and application for dynamic quantitative weighing system based on embedded Linux

Author

Hu, Pan ; Liang, Lanzhen ; Jianing Hu

Author_Institution

Sch. of Electr. Eng., Xinjiang Univ., Urumqi, China

fYear

2010

Firstpage

4917

Lastpage

4921

Abstract

In order to solve the conflict between accuracy and speed in dynamic quantitative weighing process, the neural network PID controller is designed by means of the neural network theory combined with the PID control theory for the dynamic quantitative weighing system,and proposed the new intelligent control strategy. PID (Proportion Integration Differentiation) controllers are used in a large number of industries. However, there are no satisfactory solutions about the PID parameters tuning. The optimal combination of PID controller can be realized by self-learning and memory function adjusting the control parameter K_p, K_I, K_D of PID online. This scheme has been applied to a laboratory-scale dynamic quantitative weighing system, the testing result shows the effectiveness and feasibility of the control strategy.

Keywords

Linux; control engineering computing; embedded systems; neurocontrollers; packaging; production control; production engineering computing; self-adjusting systems; three-term control; PID parameter tuning; control parameter; dynamic quantitative weighing system; embedded Linux; intelligent control; memory function; neural network PID controller; neural network theory; product packaging; proportion integration differentiation controller; self-learning; Accuracy; Analytical models; Artificial neural networks; Fasteners; Materials; Mathematical model; Performance analysis; PID controller; control strategy; dynamic quantitative weighing system; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation (WCICA), 2010 8th World Congress on

Conference_Location

Jinan

Print_ISBN

978-1-4244-6712-9

Type

conf

DOI

10.1109/WCICA.2010.5554862

Filename

5554862