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Research On The Uncoiling Part Control System Of The Precoated Steel Automatic Product Line

Posted on:2007-09-30Degree:MasterType:Thesis
Country:ChinaCandidate:Z H TanFull Text:PDF
GTID:2121360182492612Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
This thesis derives from the project "Design and Manufacture of Electric Control Device of Hanjiang 2# Precoated Steel Product Line". It comes out to be that the effect of tension control is the crucial measure to improve the quality of products through analysis. As constant tension control of the steel is the core of uncoiling part autocontrol, uncoiler constant tension control is chosen as the main research object.The tension control system this thesis discussed is an indirect tension control system based on vector control. Its essential is the torque control of the motor, namely the torque current control of the inverter. Therefore, tension current, inertia moment compensation current and friction compensation current is deduced and the principle of 1#S roller load-balanced control is elaborated in the thesis above all, and then the accomplished method is presented on the basis of that. Afterward, it sets up the models listed below respectively: model of asynchronous motor on 2-phase synchronous rotated M-T coordinate, model of inertia moment compensation and tension model, and then further sets up the overall model of uncoiler constant tension control system.Only tension of the needed variables cannot be measured or calculated directly in order to control the torque current of the inverter accurately. So it discusses to set up the tension soft-sensing model based on artificial neural network (ANN) and simulates the designed models based on BPN and RBFN in MATLAB.In addition, this thesis briefly introduces the configuration of hardware and network, setup of the inverter parameters and the communication programs in the PROFIBUS-DP network communication system.
Keywords/Search Tags:Precoated steel, Tension control, Load-balanced control, Soft-sensing, Neural network, PROFIBUS
PDF Full Text Request
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