Multivariable Disturbance Rejection Predictive Control Method Research To Desulfurization System

As an important part of China’s power system,the coal-fired power plants still occupy dominant,responsible for important tasks such as power grid peaks.However,as China’s more attention to the environment,the pollutant emission standards of large industrial processes have also become stricter,so taking off sulfur dioxide in flue gas has become an indispensable ring of flue gas treatment of coal-fired power plants.Since the desulfurization system is complicated and related to multiple variables and many disturbances,the conventional PID controller is difficult to achieve satisfactory results.With the continuous change in China’s power structure,the operating conditions of coal-fired power plants will be more and more complex,which also puts higher challenges on the desulfurization system control system.To improve the control quality of the desulfurization control system and improve the safety and economy of the system’s long-term stability operation,the algorithm for the prediction control algorithm and the disturbance rejection ability will be improved and the engineering application design of the control algorithm will be completed.In terms of predictive control algorithms,the model predictive control algorithm based on closed-loop prediction is designed based on the traditional MPC controller.By selecting a stable control effect to ensure that the prediction model is closed-loop.Subsequently,the bias is calculated by the target function to ensure the rationality of the final control action.Finally,simulations are implemented to prove this predictive control algorithm has better control performance.In terms of disturbance rejection,a single variable disturbance observer based on primary angle elevation is firstly designed and disturbance rejection ability is analyzed.Considering the limitations of the traditional single variable disturbance observer,the multivariate disturbance observer based on the state-space model are designed which can be applied directly to multivariate systems.Then the parameter optimization method of the multivariate disturbance observer is given to achieve more ideal control effects.Simulations are carried out to prove the effectiveness.In the engineering application of the desulfurization system,the feedforward control scheme of the desulfurization system is proposed to facilitate rapid response to the impact of the measurable disturbances.The development of optimized control software is completed based on Visual C++ and the corresponding modification scheme of the configuration diagram in DCS is designed.