Optimization Control of Industrial Boiler Furnace Combustion Based on Genetic Algorithm

摘要

An improved variable bias control technique is proposed to solve the problem of low combustion efficiency and boiler pollution caused by peroxide and anoxic combustion in the combustion process of industrial boilers. Using the genetic algorithm, the parameters of the offset function, fuel and air of the variable-biased double-crossing limiting combustion control system are optimized, and the optimized parameters are applied to the variable offset cross-limiting combustion control system. The furnace combustion system model was established, and the furnace combustion control scheme was designed to verify that the technology improved the combustion efficiency of the boiler and achieved the control goal of the furnace combustion, thereby achieving the purpose of curing the boiler pollution.