Study Of Fuzzy Dynamic Model And Control For Lignite In Microwave Drying Process

Coal is a sort of essential fossil fuels. The reserve of coal in china is extremely rich which can rank third in the world. However, low rank coal such as lignite account almost 50% for the total reserve of coal in china. Application of these low rank coals is limited because of high moisture content and unstable physicochemical property, to radically resolve this problem, it is necessary to remove the moisture inside the low rank coal effectively. So it is important to dry the low rank coal effectively. Traditional thermal dying technology is short of low energy efficiency, long drying time and large exhaust emission. As a sort of new energy, microwave heating is essentially different from traditional dying methods. It is characterized by high energy efficiency, short drying period, clean and pollution-free compared to traditional drying methods. As a result, microwave is a sort of promising drying method. However, the temperature in the process of microwave drying for low-rank coal is difficult to control, causing thermal runaway in practicality. Thus, application of microwave is limited greatly in dying field of low-rank coal. To prevent the occurrence of thermal runaway during the period of low rank coal by microwave and promote the application of microwave in low rank coal drying field. Consider the existed non-linear, time-variable and tight coupling property during the dying process of microwave, fuzzy dynamic model is imported to describe the drying process and model predictive control algorithm is employed to research the temperature control of drying process in this paper.The contents of research in this paper are listed below:(1) The research actuality of microwave drying for low-rank coal, mechanism modeling of microwave heating process, identification methods based on fuzzy model and temperature controlling technologies is analyzed. Then obtain the antecedent and consequence respectively of fuzzy dynamic model by fuzzy clustering algorithm and subspace identification method based on the in-out data during the microwave drying process for lignite.(2) Based on the obtained fuzzy dynamic model, temperature controller in the microwave dying process for lignite is designed by model predictive control algorithm. For the issue of existed constraints in power input of microwave drying system, the constrained temperature controller is designed to solve this problem.(3) Simulations of fuzzy dynamic model and temperature control process are disposed on the platform of MATLAB, and temperature controller is employed on the 1KW microwave drying system to verify its validity.