Title :
PID Neural Network Temperature Control System in Plastic Injecting-moulding Machine
Author :
Shu, Huailin ; Shu, Hua
Author_Institution :
Guangzhou Univ., Guangzhou
Abstract :
PIDNN (proportional, integral and derivative neural network) was first created by the author in 1997. In this paper, the author analyzes the characteristics of the temperature system of the plastic injecting-moulding machine and the performances of the PIDNN control system. The simulation results for the three-stage heater in a plastic injection machine are shown. It is proved that the PID neural network has perfect decoupling and self-learning control performances.
Keywords :
adaptive control; moulding equipment; neurocontrollers; plastics industry; temperature control; three-term control; PID neural network temperature control system; decoupling control; plastic injecting-moulding machine; proportional integral and derivative neural network; self-learning control performances; Control systems; Heat transfer; Neural networks; Neurons; Pipelines; Plastics; Temperature control; Temperature sensors; Three-term control; Transfer functions;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.554
