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

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.