Interval Type-2 Fuzzy Neural Network Control for Furnace Temperature in Municipal Solid Waste Incineration Processes

Furnace temperature plays a pivotal role in ensuring the stability of municipal solid waste incineration (MSWI), influenced by variable factors such as material composition, feeding patterns, and equipment operation. We introduce an interval type-2 fuzzy neural network (IT2FNN) control method. Initially, we analyze furnace temperature control characteristics to identity crucial operating variables. Subsequently, we construct a multiple-input single-output (MISO) model for furnace temperature using the linear regression decision tree (LRDT) algorithm. Finally, we develop an IT2FNN-based controller for furnace temperature. The effectiveness of our proposed method is confirmed through control experiments using actual MSWI process data.