The Applied Research Of Intelligence Predictive Control In Electrothermal Boiler Heating System

Heat-storage electrothermal boiler is a thermal equipment that converts electrical energy into heat energy and heats water to pressured hot water. It storages energy when the power load is low, and provides energy when the power load is high. This method not only suits the needs of the users, and also saves the energy. Meanwhile, comparing with the traditional coal boilers and fuel boilers, electrothermal boilers are more beneficial to the environment and the energy-saving. In addition, electrothermal boiler is a green environmental-friendly production. So studying a boiler heating system has important significance for energy saving and emission reduction.In this thesis, for electrothermal boiler temperature control process is in-depth studied and presents a new intelligent predictive control algorithm. In recognition, according to the data of the output sequence of the water temperature under the step response, we can get a mathematical model by using the least square offline system identification method. In the controller, considering the advantage that the dynamic matrix control will not produce static errors, a controller is designed based on Dynamic Matrix Control. A new method to optimize weighting matrix based on genetic algorithm is proposed, which can deal with the difficulty of choosing weighting matrix. Finally, under the condition of MATLAB environment, simulation of an electrothermal boiler control system is taken. Compared with the before improvement algorithms, the simulation results demonstrate the effectiveness and correctness of this method.