Furnace Temperature Control based on Adaptive TS-FNN for Municipal Solid Waste Incineration Process

In the process of municipal solid waste incineration (MSWI), the stability of furnace temperature determines the running safety and pollution emission level. The furnace temperature is influenced by different uncertainty fluctuations and strong interference. This makes it difficult to effectively control using the PID algorithm. Aiming at the above problems, an adaptive TS fuzzy neural network (FNN) furnace control method based on the furnace temperature model is proposed. First, the furnace temperature model based on the linear regression decision tree (LRDT) algorithm is established. It is multiple inputs and a single output. Then, the control algorithm based on an adaptive TSFNN controller is designed. Finally, a simulation experiment is carried out. It is based on the actual data from an MSWI plant in Beijing. The results show that the proposed method performs well in the accuracy and adaptive ability of furnace temperature control.

I. Introduction

With the acceleration of economic development and urbanization, the output of municipal solid waste (MSW) in China has increased dramatically [1]. MSW will cause serious pollution to soil, water, and air, which has affected the urban environment and social development [2]. MSW incineration (MSWI) technology has been widely used worldwide [3], [4] because of its advantage of reduction, recycling, and harmless treatment. Therefore, the study of MSWI technology is of great practical significance for environmental protection.