基于递推子空间的氧化铝浓度预测控制

为实现氧化铝浓度精确控制,基于子空间辨识及模型预测控制技术,提出一种递推子空间氧化铝浓度自适应预测控制方法. 首先,采用带遗忘因子的递推子空间算法,建立氧化铝浓度的在线预测模型,自适应地根据铝电解过程工况变化准确预测氧化铝浓度;然后,应用预测控制实现氧化铝浓度的自适应控制;最后,基于某铝厂实际生产数据开展实验研究,验证所提控制方法在氧化铝浓度精确控制上的有效性和优越性.

Predictive Control of Alumina Concentration Based on Recursive Subspace

To achieve accurate control of alumina concentration in aluminum electrolysis process, an adaptively predictive control method of recursive subspace for alumina concentration was proposed based on subspace identification and model predictive control technology. First, the recursive subspace algorithm with forgetting factor was used to establish an online prediction model of alumina concentration, which could adaptively predict the alumina concentration according to the change of working conditions. Then, the established model was applied to predictive control to achieve adaptive control of alumina concentration. Finally, based on the actual production data of an aluminum plant, experimental research was carried out to verify the effectiveness and superiority of the proposed control method for precise control of alumina concentration.