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首页> 外文会议>IEEE Conference on Decision and Control >Model Free Adaptive Predictive Control of Multivariate Molten Iron Quality in Blast Furnace Ironmaking
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Model Free Adaptive Predictive Control of Multivariate Molten Iron Quality in Blast Furnace Ironmaking

机译：高炉炼铁多元铁水质量的无模型自适应预测控制

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摘要

The complicated physical and chemical reactions in the internal complex operating environment of smelting process and the Blast Furnace (BF) have led to the difficulty of establishing the model-based controllers. Therefore, model free control methods should be used that meet the actual needs of the engineering systems. However, due to the sparse characteristic of the molten iron quality (MIQ) data in BF ironmaking, traditional model free adaptive control based MIQ control methods cannot control such a complex industrial system with strong nonlinear time-varying dynamics. In this paper, an extended and compact form dynamic linearization (CFDL) based model free adaptive predictive control (MFAPC) scheme (CFDL-MFAPC) is proposed for multivariate MIQ indices by generalizing the CFDL-MFAPC method only for SISO system to MIMO system. Two groups of verification experiments are performed to evaluate the performance of the controller. The results show that the proposed method has not only a better control performance than the compared traditional CFDL based model free adaptive control method and data-driven model predictive control (MPC) method, but also can guarantee the bounded-input bounded-output stability of the MIQ output of the control system for BF ironmaking process.
机译：在冶炼过程和高炉内部复杂的操作环境中，复杂的物理和化学反应导致难以建立基于模型的控制器。因此，应使用满足工程系统实际需求的无模型控制方法。然而，由于高炉炼铁过程中铁水质量（MIQ）数据的稀疏特性，传统的基于无模型自适应控制的MIQ控制方法无法控制这种具有强大非线性时变动力学的复杂工业系统。本文通过将CFDL-MFAPC方法推广到SISO系统到MIMO系统中，针对多变量MIQ指数提出了基于扩展和紧凑形式动态线性化（CFDL）的无模型自适应预测控制（MFAPC）方案（CFDL-MFAPC）。进行两组验证实验以评估控制器的性能。结果表明，该方法不仅具有比传统的基于CFDL的无模型自适应控制方法和数据驱动模型预测控制（MPC）方法更好的控制性能，而且可以保证有界输入的有界输出稳定性。高炉炼铁过程控制系统的MIQ输出。

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