Data Reconciliation And Predictive Control With Applications To Ammonia Flue Gas Desulfurization Process

The reduction of SO₂ emission in thermal power industry is not only of great practical significance to environmental protection,but also an urgent need for the country to establish a resource-saving and environment-friendly enterprise.The Phase I desulfurization system of the Yangtze Petrochemical Thermal Power Plant uses ammonia as an absorbent to remove SO2 in the flue gas.Because the ammonia desulphurization process involves complex physical and chemical reactions,there are great inertia and nonlinear characteristics in the desulfurization system,which leads to data inaccuracy and low control levels during the current operation of the desulfurization system.In addition,traditional data processing methods and control strategies are difficult to achieve satisfactory control effects.Therefore,new data correction strategies and advanced control strategies need to be studied.In this paper,according to the object characteristics and operation requirements of ammonia desulphurization system,the applicable data reconciliation technology and constrained MPC with zone control are studied.The main research contents include:1.In order to obtain the operating data that can accurately reflect the actual dynamic process of the desulfurization system,combining with the robust estimation function,a new type of data reconciliation strategy based on an improved wavelet threshold denoising method is proposed to realize the successive removal of gross errors and random errors in the measurement data.Through simulation experiments and on-site examples,the accuracy and reliability of the algorithm is verified,which provides reliable data foundation for subsequent researches on system characteristics and optimization control.2.Aiming at the actual control needs of ammonia desulfurization system,a constrained MPC with zone control is proposed.This strategy uses the augmented state space model as the description of the system.Under the cost function based on zone control,the adjustment of outlet SO2 concentrations and circulating slurry pH can be achieved by coordinating the flow of ammonia of the two desulfurizers.In order to enhance the robust performance of the algorithm,an adaptive robust Kalman filter based on simplified Sage-Husa is further proposed.Finally,the identification model is used as the control object,and the control performance and robust performance of the proposed algorithm are evaluated through simulation experiments.3.Advanced control software was developed and successfully applied in a real ammonia desulfurization system.According to the application results,the functions of the software in valve characteristic fitting,feedforward signal design,and purge signal processing are improved,and the on-site long-term operation is realized.By comparing the running indices under manual control and advanced control,the actual application value of the software is evaluated.