| Induction heating furnace is an efficient equipment for metal heat treatmentprocess, it shoulds not only provide preset power, but also maintain a certain frequency.The induction heating furnace is prone to generate the phenomenon of magnetic fluxleakage. The power supply voltage and current may also interfere with the heatingprocess. So the control system should consider the above characteristics, and thecontrol system performance is becoming one key problem to the induction furnace.The most important performance index in the induction heating system is thetemperature varying of the workpiece. In this paper, induction quenching furnace isconsidered. The controller is designed to improve the performance of the temperaturecontrol system in this thesis.As for the parallel resonant induction quenching furnace, the temperature modelis built by the mechanism of induction quenching furnace heating system analysis,which is based on the principle of electromagnetic induction and the knowledge ofheat transfer theory. The system model is simplified as a second-order inertial system.The dynamic and static characteristics are analyzed by simulation, which providesbasis for the controller design.Considering the temperature characteristics of induction quenching furnaceprocess, the temperature control system is analyzed. A fuzzy adaptive PID algorithm isdesigned based on the fuzzy inference and PID control principle. And the controlsystem is simulated and analyzed. Compared with the classic PID control and purefuzzy control, fuzzy adaptive PID control takes into account the fast of fuzzy controland the accuracy of PID control. The performance of fuzzy adaptive PID is superior tothe classic PID and fuzzy control.To further improve the control system performance and the quality oftemperature tuning, a soft switching fuzzy PID controller is designed for quenchingfurnace temperature control system. Because the fixed threshold-based hard switching control is prone to produce disturbance near the switching point, it is not desired tosmooth temperature control. The proposed method is based on the soft switchingstrategy based on weighting factor. The weighting fator is studied as a focus, and anexponential weighting factor based on temperature regulation error is designed.Compared with fuzzy adaptive PID controller, the simulation results show that the softswitching controller has advantages in stability, load adaptability, etc. which provides areference for engineering design of the quenching furnace temperature control system. |
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