Design On Temperature Control System Of Heat Preservation In Bidirectional Pull Machine

In this paper, the heat preserving cavity of bidirectional pull machine is study carrier and temperature stability in the heat preserving cavity is studied. Temperature plays a vital role in the whole process that the bidirectional pull machine works. It is important to maintain a specific temperature, stable and persistent, to gain the good quality of the glass.It is difficulty to establish a mathematical model for the temperature which is uncertainty, big inertia, and serious non-linearity to control. The traditional control methods in high-precision temperature control have been unable to achieve control requirements, which in the first chapter of introduction have been introduced. According to the specific control problems and requirements, a fuzzy neural network control algorithm has been developed. In the second chapter, the basis of the control algorithm theory has been introduced and the superiority of this algorithm has been expounded. In the third chapter the hardware and software environment of temperature control algorithm in the heat preserving cavity of bidirectional pull machine. The specific structure and layout of the heat preserving cavity, the wind road and heating system has been introduced. Temperature control system uses the parallel control technology with IPC and PLC.IPC computing tasks and PLC communication control tasks have been described respectively and the software environment of control system has been wholly designed. On the basis of combination algorithm theory with hardware and software environment, temperature control programme of the heat preserving cavity has been determined and the specific fuzzy neural network algorithm has been designed according to the actual control requirement in the fourth chapter. This control algorithm could be used not only for the mathematical model of controlled object being not established, but also possesses an online self-learning ability. So this control algorithm resolves the control difficulty of temperature stability in the working time and meet the production requirements.In this paper the fuzzy neural network algorithm what temperature control used has been simulated with the Matlab software. Firstly these parameters in the structure of the algorithm were trained, so the optimal control parameters occurred and the fuzzy rules in fuzzy control being optimized. On the basis of two above the algorithm was simulated in the end. From the simulation plan can be seen: at the time of using fuzzy neural network algorithm, the system overshoot is small and there were no fluctuation of volatility in the steady state and steady-state warp. Practice shows that the control method is feasible and can achieve the required control accuracy.