Remote Generalized Predictive Control Of Metering Pump Flow Based On Differential Evolution

High-performance automation control of various process industry is a research hotspot in the field of industrial control.In the actual production process,the mixing process of fluid materials is often involved.Based on the requirements of different production processes,industrial diaphragm metering pump has gradually become an important production actuator,mainly for quantitative transportation and proportional dosing of fluids.In order to improve the performance of the metering pump,the literature in recent years has focused more on optimizing the mechanical structure of the metering pump.Few people have considered exerting better control algorithms in the field of pump control.In fact,an appropriate control algorithms and control scheme can greatly save production costs and improve economic efficiency.In this context,this paper takes the industrial diaphragm metering pump as the research object,considering the requirements of remote precise control of flow in actual production,designs a flow optimization control scheme based on the idea of model control theory,and builds a remote fluid dosing system based on the metering pump.The main research work of this paper is as follows:(1)Based on the internal mechanical structure of the metering pump,the principle of the flow regulation is analyzed.Considering the unsteady dynamic transition relationship between the pump flow and the motor speed,the corresponding identification experiment is designed to obtain the dynamic model,including the design of identification signal,a data preprocessing method based on wavelet analysis combined with threshold is involved to preprocess the measured flow data.Based on the prior parameter model of the system,the system is identified based on neural network and improved differential evolution algorithm.The simulation results prove the superiority of the algorithm,actual data and the model output signal fits perfectly,which verifies the reliability of the model.(2)According to the identified dynamic model of metering pump,an online flow regulation optimization algorithm is designed.Based on traditional generalized predictive control algorithm,the differential evolution algorithm is introduced to deal with the constraints of the actual system.Optimal speed is calculated online.Considering the pulsating impact load during the actual working process of the metering pump,the reasons that may affect the local motor speed are analyzed.The speed compensation controller based on fuzzy control is designed to reduce the flow error caused by the inaccurate speed.Combining the optimal speed to realize the online optimization of the metering pump flow.(3)The flow control scheme proposed in this paper is tested in the remote fluid dosing platform built by the laboratory.The upper computer flow optimization algorithm is integrated into the self-developed monitoring software via JAVA,and the speed compensation algorithm is compiled by C in the local metering pump variable frequency controller.The Gateway can realize the remote interaction of control information.The performance of the proposed scheme is evaluated by simulating the different working conditions,which can meet the requirements of the general process industry.