Temperature is a critical controlled parameter in industrial production and daily life. Precise monitoring of temperature ensures the stable and efficient operation of instruments such as constant temperature chambers and reaction furnaces. In the field of food packaging, thermal sealing is commonly used for sealing packages, and the temperature of the sealing process largely determines the quality of food packaging. Optimal packaging seal quality can only be achieved with the use of the best temperature for thermal sealing in packaging machines. Due to the significant influence of heat transfer inertia, heating and cooling rates, voltage fluctuations in actuators, and various other disturbances during the operation of packaging machines, thermal sealing temperature control has become one of the key research areas in the field of food packaging.
Commonly used methods for controlling the temperature of the sealing cutter in packaging machines are based on fuzzy PID control. The PID control algorithm adjusts the parameters of the control process through three parameters: proportional, integral, and derivative. Although the PID control algorithm has the advantages of fast dynamic response and simple structure, it is challenging to control systems with complexity, severe time variability, and nonlinear states.
Another method involves designing an automatic packaging machine temperature control method based on Radial Basis Function (RBF) neural networks. Utilizing RBF neural networks can enhance parameter regularization and achieve precise adjustment due to their nonlinear mapping and self-learning capabilities. This method is more suitable for complex control systems, but the control process may be time-consuming and difficult to achieve real-time control.
The Jill Group proposes the use of Programmable Logic Controllers (PLCs) with microprocessors as the control core. PLCs are industrial automatic control devices that fully consider automatic control technology, computer technology, and communication technology. PLCs can achieve various equipment parameter controls based on user requirements through programmed programs, providing high control effectiveness. By utilizing programmable memory, PLCs execute various operation instructions such as sequence control, logic operations, technology, timing, and arithmetic. They can also automate control of equipment and circuits through input and output of digital and analog signals.
Additionally, the PID control algorithm outputs control signals through integral, proportional, derivative, and other logic operations, which are then used to control parameters such as temperature and pressure. The JILL Group combines RBF neural networks with PID control algorithms and applies them to PLC controllers, thereby designing a method for temperature control of thermal sealing in food packaging machines based on PLC technology, achieving automatic adjustment and control of thermal sealing temperature in food packaging machines.
