基于嵌入式集散电气系统的啤酒生产过程控制与应用研究
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摘要
在现代工业生产中,为提高生产效率、降低生产成本、提高产品质量等,普遍要求实现电气设备的自动化和智能化。为了解决复杂的工业现场控制类问题,一般选择嵌入式集散电气控制系统达到控制目的。模拟量的嵌入式集散测控技术是实现电气设备自动化和智能化的核心技术。
根据啤酒生产的工艺要求和特点,设计了高精度、低成本的啤酒糖化和啤酒发酵嵌入式集散电气控制系统。系统采用自主研发的智能化嵌入式数据终端处理器为控制终端,与工控计算机组网,构成嵌入式集散电气控制系统。
针对非线性模拟量测量问题,提出了基于阈值可变神经元的模拟量检测方法。阈值可变人工神经元的阈值随神经元的输入信息和输出结果而变化,为解决单调非线性模拟量精确测量问题提供了理论依据。通过研究,给出了阈值可变人工神经元权值和阈值的分段线性化和分段变斜率两种训练方法和编程思路,可精确地完成非线性模拟量的检测,而且可行性很强。
依据系统对模拟量实时控制要求,提出了基于控制微元的统计自适应增量控制方法。给出量化控制状态统计图的获取方法;分别找出扩展控制微元的统计稳定系数、平均统计状态偏差、统计趋势、统计超调、尾偏差等参数与调节增量之间的关系;确定了统计控制策略及其最优化条件;给出统计预测自适应记忆增量控制器的设计方案;详细介绍了相关参数的选择方法及可能出现问题的处理方法。基于控制微元的统计自适应增量控制方法在啤酒生产的过程控制中取得了良好的控制效果。
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.
根据啤酒生产的工艺要求和特点,设计了高精度、低成本的啤酒糖化和啤酒发酵嵌入式集散电气控制系统。系统采用自主研发的智能化嵌入式数据终端处理器为控制终端,与工控计算机组网,构成嵌入式集散电气控制系统。
针对非线性模拟量测量问题,提出了基于阈值可变神经元的模拟量检测方法。阈值可变人工神经元的阈值随神经元的输入信息和输出结果而变化,为解决单调非线性模拟量精确测量问题提供了理论依据。通过研究,给出了阈值可变人工神经元权值和阈值的分段线性化和分段变斜率两种训练方法和编程思路,可精确地完成非线性模拟量的检测,而且可行性很强。
依据系统对模拟量实时控制要求,提出了基于控制微元的统计自适应增量控制方法。给出量化控制状态统计图的获取方法;分别找出扩展控制微元的统计稳定系数、平均统计状态偏差、统计趋势、统计超调、尾偏差等参数与调节增量之间的关系;确定了统计控制策略及其最优化条件;给出统计预测自适应记忆增量控制器的设计方案;详细介绍了相关参数的选择方法及可能出现问题的处理方法。基于控制微元的统计自适应增量控制方法在啤酒生产的过程控制中取得了良好的控制效果。
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.
引文
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