Intelligent Optimization Control Strategy for Secondary Pollution of Flue Gas in Municipal Solid Waste Incineration

Abstract

Aiming at the problem of serious secondary pollution caused by improper control strategy in the waste incineration process, this paper proposes an intelligent optimization control strategy for secondary pollution of flue gas in municipal solid waste incineration. Firstly, the control difficulties of waste incineration and cybernetic characteristics of combustion process in incinerators are analyzed, and the basic algorithm based on human simulated intelligent control is proposed accordingly. Then, genetic algorithm is used to improve particle swarm algorithm and search ability in wide space, which can avoid the premature phenomenon of local optimum. Finally, improved particle swarm algorithm is utilized to optimize the parameters in human simulated intelligent control algorithm to realize intelligent optimization control in the waste incineration process. Based on MATLAB simulation platform, experimental results show that when delay parameters and time constant change significantly, there are large disturbances, and the process response of proposed strategy is fast and stable, which is superior to other comparison strategies.