Interval Type-Ⅱ FNN-based Furnace Temperature Control for MSWI Process

Addressing the challenge that it is difficult to effectively control the furnace temperature in the municipal solid waste incineration (MSWI) process, a furnace temperature control method based on interval type-Ⅱ fuzzy neural network (IT2FNN) is proposed. First, the furnace temperature control characteristics were analyzed to determine the key operating variables that affect it. Subsequently, according to the above operational variables, a multiple-input single-output (MISO) furnace temperature model was fomulated based on the linear regression decision tree (LRDT). Finally, an IT2FNN controller with adaptive parameter learning was developed and its stability was proven. The experimental results of model construction and control on the MSWI process dataset confirm the efficacy of the proposed method.