The regulation quality of boiler denitrification system control has great significance for unit safety and economy operation. On the basis of the time-varying parameters of the unit load

this article presents the denitrification system's nonlinear model identification method. The linear parameter time-varying(LPV) model was established by the historical data

which can reflect the global dynamic properties of the object. Moreover

to optimize the high-dimensional parameters

the evolutionary acceleration factor was added into the quantum particle swarm optimization algorithm. The modified algorithm's optimization efficiency was improved

and the optimization effect was more close to the optimal value. The high efficiency of this algorithm was verified through high-dimensional standard function test. Finally

this solution was applied to the denitrification control system modeling of a 600 MW unit

the identification results show that the denitrification conversion model is valid

and the program is feasible.