Modeling And Predictive Control Strategy Research Of Supercritical Unit

Supercritical unit has higher efficiency and lower emissions than subcritical unit,but its dynamic characteristics are more complex.n order to improve the control efficiency of supercritical unit,the advanced controllers should be adopted.However,the advanced controllers always need a suitable model with high accuracy and simple structure.So it is significant to research the modeling approach and related advanced control algorithm of supercritical unit.Coordinated control system(CCS)is the control core of supercritical unit,and its control result can affect the performance of unit.Therefore,CCS is treated as the main researched object,its modeling approach and related constrained predictive control algorithm are studied.Firstly,in order to get the suitable model of CCS with high accuracy and simple structure,an improved T-S fuzzy model identification approach is proposed in this paper.The improved entropy cluster algorithm is applied to identify the premise parameters which can automatically determine the cluster numbers and initial cluster centers by introducing the concept of a decision-making constant and threshold.Meanwhile,the edge data points will not be selected as cluster centers.The concluding part is adopt a new structure.The cluster centers are treated as the operating points and the incremental data around the cluster center is employed to get the local linear model.Due to using the new structure,the local linear model and the global model can both be directly used to design the advanced controllers.Then,for the purpose of handling the complex characteristics of CCS,the constrained predictive control is researched.The study of simulation is carried by using the local linear model built in this paper.From the simulation results,it can be concluded that constrained predictive control has great control effect and the strong anti-jamming ability.Finally,because the CCS of supercritical unit is a nonlinear system with the variation of operating points,the single linear controller cannot achieve good control effect.For solving the influence of nonlinearity,the nonlinear predictive control algorithm based on T-S fuzzy model is adopted.n this algorithm,T-S fuzzy model is converted into a time-varying CAR MA model,and this time-varying model is combined with constrained predictive control algorithm.Simulation results show that the proposed approach has higher tracking speed and less overshoot in a wide range operation of supercritical unit.