Disturbance Rejection Control Of SCR Denitrification System Based On Extended State Observer

With the increasingly stringent requirements of global environmental protection,the SCR flue gas denitrification system in thermal power plants is facing more severe challenges,but the SCR flue gas denitrification system in thermal power plants has the characteristics of large inertia,large delay,multi-disturbance and uncertainty,which makes it a hot and difficult point for researchers to explore more effective modeling methods and control algorithms with strong anti-interference ability.Taking the linear extended state observer as the main line,this paper carries out the theoretical research on the intelligent identification method of model parameters based on extended state observer and the design of auto disturbance rejection controller based on improved sparrow search algorithm.The experimental simulation and engineering implementation are carried out based on the actual collected SCR system operation data.The main work of this paper is as follows:This paper describes the basic theoretical knowledge of continuous system discretization,data preprocessing under zero initial conditions,mutual information estimation of pure delay time,extended state observer,sparrow search algorithm,ESObased least square identification method,linear auto-disturbance rejection controller and so on.In view of the deficiency of sparrow search algorithm(SSA),quantum and Levy flight strategy are integrated into SSA,and an optimized intelligent algorithm is proposed: hybrid quantum sparrow search algorithm(QSSA).Secondly,aiming at the object with pure delay and the low accuracy of least square identification based on ESO,an intelligent identification algorithm of model parameters based on improved ESO is proposed.Finally,the SCR denitrification model under the load of 280 MW and 600 MW is established by using the actual operation data of SCR denitrification system.In order to improve the anti-interference ability and set point tracking ability of a class of controlled objects with large inertia,large delay and uncertainty,an improved auto-disturbance rejection(including pure delay link and FOPDT)control method based on QSSA is proposed.Because the initial optimization range of parameters is difficult to determine and parameter tuning is difficult,by consulting the literature,many methods of manually tuning PID and second-order ADRC parameters are learned,and the range of controller parameters is preliminarily determined,and then QSSA optimization algorithm is used to optimize controller parameters.Finally,the improved auto disturbance rejection control based on QSSA is applied to the SCR denitrification system model,and the step simulation,internal and external disturbance analysis and model change test are carried out.The results show that the proposed method can achieve better control effect,stronger stability and anti-interference ability than PID and ADRC.This paper introduces the intelligent optimization control platform developed by ourselves,and based on the intelligent optimization control platform,designs and implements the improved ADRC control algorithm module,and then takes the SCR denitrification system model under 280 MW as the object,and builds the simulation logic diagram of improved ADRC-PI and PID-PI cascade control in the platform,and carries on the step simulation and control quantity disturbance experiment.The experimental results prove the effectiveness,superiority and feasibility of the proposed improved ADRC algorithm,and show that the algorithm has a good industrial application prospect.