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Soft-sensing Design Based on Semiclosed-loop Framework 被引量：2

基于半闭环框架的软测量设计(英文)
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摘要 Soft-sensing is widely used in industrial applications. The traditional soft-sensing structure is open-loop without correction mechanism. If the working condition is changed or there is unknown disturbance, the forecast result of soft-sensing model may be incorrect. In order to obtain accurate values, it is necessary to carry out online correction. In this paper, a semiclosed-loop framework (SLF) is proposed to establish a soft-sensing approach, which estimates the input variables in the next moment by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and robustness than other open-loop models. Soft-sensing is widely used in industrial applications. The traditional soft-sensing structure is open-loop without correction mechanism. If the working condition is changed or there is unknown disturbance, the forecast result of soft-sensing model may be incorrect. In order to obtain accurate values, it is necessary to carry out online correction. In this paper, a semiclosed-loop framework （SLF） is proposed to establish a soft-sensing approach, which estimates the input variables in the next moment by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and robustness than other open-loop models.
作者 汤奇峰 李德伟 席裕庚 尹德斌
机构地区 Department of Automation Shanghai Xinhua Control Technology (Group) Co.
出处 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2012年第6期1213-1218,共6页 中国化学工程学报（英文版）
基金 Supported by the National Natural Science Foundation of China (60934007, 61074060, 61104078) the Research and Innovation Project of Shanghai Education Commission (11CXY08) the State Key Laboratory of Synthetical Automation forProcess Industries
关键词 soft-sensing neural network semiclosed-loop framework 控制框架 半闭环 测量基 设计 预测模型 开环模型 软测量模型 软测量方法
分类号 TP274 [自动化与计算机技术—检测技术与自动化装置]
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共引文献41

同被引文献15

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引证文献2

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Chinese Journal of Chemical Engineering
2012年 第6期

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