The Intelligent Control System For Infrared Shrink Film Machine

PID control algorithm is widely adopted by traditionally temperature control but does not suitable for far infrared heating, the reason is that there are many drawbacks existing in temperature control of far infrared heating devices, i.e., big overshoot, difficult parameter setting, long regulation time, poor anti-interference ability. Far infrared heating machine is mainly used for constant temperature heating and film Shrinking, the body’s temperature control must ensure the constant temperature, so the shrink film quality can only be guaranteed. One algorithm of PID controller based on BP neural networks is designed to realize control parameter self-learning and self-adjusting in the presented paper, which can improve the temperature control performance, and solve the problem of temperature control of shrink film machine.In the given paper, the hardware platform is designed like this, micro-controlled was adopted as control core, RS-232serial port was adopted as communication interface to PC, K-type thermocouples were used as temperature acquision system, what is more, solid-state relays were adoped for heating the box body, and electronic governor SSA4-3/200was adopted to realize the motor with speed stepless adjusting. The devices drive the motor to realize stepless speed regulating. In addition, in this paper introduces the design of hardware circuit and the flow chart of system control software,based on the control system, add intelligent control algorithm to achieve real-time control of the heating system. The improved hardware anti-jamming capability of the control system be strengthened, improved the cigarette case plastic film production efficiency and product quality. On the software and algorithm design, this paper Guided by the principle of neural network, an intelligence PID controller based on neural network is devised and applied to control of constant temperature heating box system. Using the capacity of arbitrary nonlinear expressiveness, neural network can help to achieve the best control through learning systemic performance and adjusting automatically PID parameter.enhanced the ability of the robustness, and raised the cigarette plastic film production efficiency and product quality.Finally, to identify the effectiveness of the presented study, MATLAB was adopted for simulation and comparison between fuzzy controller traditional PID and Neural network PID controller, the result showed that the priority control effects of Neural Network PID controller, which have higher accuracy and stronger adaptability, and can get satisfied control result, improve the existence far infrared heating box parameters difficult tuning, big overshoot, long adjusting time, poor anti-interference ability, and the setting of temperature values can be adjusted and looped, the system can meet the requirements of cigarette case plastic film, and the temperature can be controlled about200℃with the accuracy of-1.5%～3%.