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Research On Process Control Of Beer Production Based On Embed And Distributed Electrical System

Posted on:2009-01-16Degree:DoctorType:Dissertation
Country:ChinaCandidate:B SunFull Text:PDF
GTID:1118360272999646Subject:Motor and electrical appliances
Abstract/Summary:PDF Full Text Request
In modern industry, automatization and intelligentiztion are commonly demanded for electrical equipments, which aim to enhance efficiency, to reduce cost and to improve quality of product. Embed and distributed electrical control systems are widely used to solve complicated problems in locale. The key technology to realize automatization and intelligentiztion of electrical equipments is adopting embed and distributed detecting method for analog signals.An embed and distributed electrical control system for putting sugar into beer with high precision and low cost is designed, according to technologic request and characteristic. The system adopts self-developed and intelligent embed data processor, which combine with computer for industrial control.A detecting method of analog variable based on variable threshold value neuron method is proposed, which is used for measuring nonlinear analog signals. Variable threshold value artificial neuron is that the threshold value of variable threshold value artificial neuron varies along with input and output. Moreover, it provides academic basis for solving problems of precise measurement for nonlinear and single value analog signals. Subsection linearization and subsection variable slope methods for training threshold value and weight coefficient are researched. They are prone to realize on micro-unit, and are feasible for detecting analog signals.A statistical and adaptive increment control method based on control-cell, which is of perfect real-time control effect, is proposed. The statistical control tactics and its optimum condition are established. The method for obtaining statistical figure of quantization control is given. The relationship between regulated increment and control parameters is found, with the parameters including average deviation statistics, statistical trend, statistics overshoot, and end deviation. The design of statistical and adaptive memory incremental controller is carried out. The method of how to choose relative parameters and how to deal with problems encountered are full discussed.
Keywords/Search Tags:intelligent control, artificial neuron, distributed control system, embed system
PDF Full Text Request
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