Intelligent Control System of Multi-segments Continuously Sintering Furnace

Data‐driven modelling methods in sintering process: Current research status and perspectives

“…Li et al [30] Dynamic time feature expanding and extracting framework for FeO content prediction Liu et al [31] LSTM network for the chemical composition prediction Gao et al [32] Integrated model combining PCA with GA for tumble strength prediction Ye et al [33] TS model combined with a local thermal non-equilibrium (LTNE) model for tumble strength prediction Du et al [34] Fuzzy time series model for BTP prediction Yan et al [27] Denoising spatial-temporal encoder-decoder network for BTP prediction Chen et al [35] Hybrid just-in-time learning soft sensor (HJITL-SS) for CCR prediction Hu et al [36] Customized kernel-based Fuzzy C-Means (CKFCM) clustering method for CCR prediction Control Du et al [37] A fuzzy controller using the Mann-Kendal for BTP control Wang and Wu [38] A two-level hierarchical intelligent control system for BTP control Chen et al [39] Takagi-Sugeno (T-S) fuzzy model for BTP control Ying et al [40] Proportional-integral-derivative (PID) neural network for ignition temperature control Cao et al [41] An expert control system for ignition temperature control Optimization Zhou et al [42] Multi-objective and multi-time-scale optimization model for CCR Huang et al [43] A low-carbon and low-cost blending scheme for reducing the energy consumption Hu et al [44] An online optimization model for CCR Wu et al [45] An intelligent integrated optimization system (IIOS) for proportioning Wang et al [46] Cascade multi-objective optimization model (CMOM) for proportioning Abbreviations: BTP, burn-through point; CCR, comprehensive carbon ratio; GA, genetic algorithm; LSTM, long short-term memory; PCA, principal component analysis.…”

“…Considering the fluctuations in ignition temperature, an intelligent control strategy based on a particle swarm optimization (PSO)-Elman prediction model was presented, and the experimental results verified its effectiveness. [90] As continuous sintering is affected by many factors, Cao et al [41] designed an expert control system for continuous sintering based on temperature field analysis. Some other studies are in these references.…”