Abstract
The cement industry is one of the main sources of NOx emissions, and automated denitration systems enable precise control of NOx emission concentration. With non-linearity, time delay and strong coupling data in cement production process, making it difficult to maintain stable control of the denitration system. However, excessive pursuit of denitration efficiency is often prone to large ammonia escape, causing environmental pollution. A multi-objective prediction model combining time series and a bi-directional long short-term memory network (MT-BiLSTM) is proposed to solve the data problem of the denitration system and achieve simultaneous prediction of NOx emission concentration and ammonia escape value. Based on this model, a model predictive control framework is proposed and a control strategy of denitration system with multi-index model predictive control (MI-MPC) is built based on neural networks. In addition, the differential evolution (DE) algorithm is used for rolling optimization to find the optimal solution and to obtain the best control variable parameters. The control method proposed has significant advantages over the traditional PID (proportional integral derivative) controller, with a 3.84% reduction in overshoot and a 3.04% reduction in regulation time. Experiments prove that the predictive control framework proposed in this paper has better stability and higher accuracy, with practical research significance.
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Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Funding
This work was supported by the National Natural Science Foundation of China (Grant No. 62073281), the Natural Science Foundation of Hebei Province (Grant No. F2022203088), the Natural Science Foundation of Hebei Province (Grant No. F2023203029), and Hebei innovation capability improvement plan project (Grant No. 22567619H).
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Xiaochen Hao: conceptualization, formal analysis, funding acquisition, supervision. Xinqiang Wang: writing — original draft, visualization, data curation, software. Xing Wang: project administration, software, methodology. Yukun Ji: writing — review and editing, data curation.
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Hao, X., Wang, X., Wang, X. et al. Multi-index control strategy from cement calcination denitration system: a model predictive control method for combined control of nitrogen oxide and ammonia escape. Environ Sci Pollut Res 31, 28997–29016 (2024). https://doi.org/10.1007/s11356-024-32996-6
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DOI: https://doi.org/10.1007/s11356-024-32996-6