Soft-sensing Design Based on Semiclosed-loop Framework
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 value...
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| Veröffentlicht in: | Chinese journal of chemical engineering 2012-12, Vol.20 (6), p.1213-1218 |
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| container_title | Chinese journal of chemical engineering |
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| creator | 汤奇峰 李德伟 席裕庚 尹德斌 |
| description | 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. |
| doi_str_mv | 10.1016/S1004-9541(12)60610-7 |
| format | Article |
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| ispartof | Chinese journal of chemical engineering, 2012-12, Vol.20 (6), p.1213-1218 |
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| language | eng |
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| subjects | Calibration Chemical engineering Disturbances Estimates Mathematical models neural network On-line systems Online Robustness semiclosed-loop framework soft-sensing 半闭环 开环模型 控制框架 测量基 设计 软测量方法 软测量模型 预测模型 |
| title | Soft-sensing Design Based on Semiclosed-loop Framework |
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