Dynamic Data Reconciliation Technology For Improving The Performance Of Control System And Its Application

Due to the complexity of the actual industrial system production environment,the performance of the control system is often difficult to meet the increasing production requirements.In general,measurable and unmeasurable external disturbances are considered in the system environment during performance analysis.In fact,in the measurement process of the feedback loop,the Gaussian or non-Gaussian measurement noise generated by the sensor will also affect the performance of the control system.This paper considers and analyzes the influence of Gaussian/non-Gaussian measurement noise and external disturbance on system performance.For feedback system,feedforward-feedback system and nonlinear system,a dynamic data reconciliation(DDR)filtering technology is proposed to improve the control system performance.The research work and innovations of the paper includes:1.Taking generalized minimum variance control(GMVC)as the performance standard,the influence of Gaussian and non-Gaussian measurement noise on the controller performance assessment(CPA)of single-input single-output(SISO)and multiple-input multiple-output(MIMO)feedback system is considered.Based on the uncertainty of measurement and model prediction,a DDR technology based on Bayesian estimation is designed to improve system performance.The application of the DC-AC coverter control system in the simulation experiment verifies the effectiveness of DDR.2.Since DDR is an optimal estimation method based on Bayesian formula,when the external disturbance and measurement noise of the feedback system are both non-Gaussian distribution,DDR is redesigned to improve the system performance.In order to verify the performance improvement effect of DDR under different indexes,the step response of the system is compared in the simulation and DDR is further applied to the DC-AC converter system to improve the output voltage.The results show that DDR can also reduce the influence of non-Gaussian measurement noise and external disturbance on the system performance.3.For the feedforward-feedback system including disturbance compensation,the influence of Gaussian and non-Gaussian measurement noises on the performance of SISO and MIMO systems are discussed.DDR can determine the optimal feedback output of the system by reconciling model prediction information and measured information.In order to reduce the impact of measurement noise,consider extending the DDR technology to feedforward-feedback system to improve system performance.In the simulation,the comparison of the system output and the application of DDR in the DC-AC converter system verify the performance improvement effect of DDR.4.Nonlinearity is widely used to describe the uncertain process of the system.By improving the accuracy of measured feedback,DDR can improve the control performance of the nonlinear system.Considering the influence of Gaussian and non-Gaussian measurement noises on the performance of nonlinear system,DDR technology is also extended to nonlinear system to improve the control performance.In the simulation,the step response of exponential filter and DDR filter is compared to highlight the advantages of DDR.In view of the measurement noise in the feedback process,this paper uses DDR filtering technology to reduce the influence of measurement noise on the system performance.Compared with exponential filter,DDR is a model-based filtering technology.The results of theoretical analysis and simulation experiments show that,DDR can more effectively improve the performance of the control system under the influence of measurement noise.