An Improved Hierarchical Fused Fuzzy Deep Neural Network Method for Controlled Object Model of Furnace Temperature for MSWI Process

Addressing the challenge of precisely controlling furnace temperature, this study introduces a modeling strategy based on an enhanced hierarchical fused fuzzy deep neural network (HF-FDNN) model. Initially, an analysis of the control characteristics of furnace temperature identifies key manipulated variables (MVs). Subsequently, we refine the HF-FDNN algorithm within the task-driven layer to develop a model for furnace temperature control. Finally, we validate the effectiveness of proposed method through experimental results derived from real municipal solid waste incineration (MSWI) process data.