Research On Evaporator Temperature Control Systems

Evaporator is a very important equipment both for energy utilization and energy saving. It is widely applied in many industrial departments. Accurate measurement and effective control of the working fluid temperature at the outlet of evaporator are important conditions of high quality, energy-saving and safety in the process control system of evaporator. Therefore, the control of the working fluid temperature at the outlet of evaporator is a key issue in industrial process. The control of the working fluid temperature at the outlet of evaporator is studied in this paper. The control task is to make the temperature of working fluid from the evaporator approach to the set-point by manipulating the velocity of heat carrier in order to guarantee the system operate safely and make full use of energy.Presently, the evaporator model is too simple to describe the dynamic characteristics of evaporator, or too complex to design controller. Therefore, a moving boundary model is investigated for the evaporator in this paper. The simulation in MATLAB/SIMULINK demonstrates that the moving boundary model could capture the length of different phase sections in evaporator dynamically and reflect the operation condition of evaporator accurately.Then, a neuro-PID control scheme based on BP neural network is proposed to deal with nonlinearity of evaporator temperature control systems. After analyzing the characteristic of fuzzy theory and neural network, fuzzy neural network supervisory control, which is based on the RBF neural network, is proposed. In order to show the advantages of the proposed schemes, the PID controller and RBF neural network supervisory controller are designed respectively. And the simulated results show that the proposed schemes improve the static and dynamic performance of the control system.