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An Intelligent Control System for Continual Carbonation Decomposition Process of Sodium Aluminate Solutions Based on Expert and Prediction Strategy

机译:基于专家和预测策略的铝酸钠解决方案持续碳化分解过程智能控制系统

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In alumina production using the sintering process, it is one of the key processes to produce Al(OH)3using the method of continual carbonation decomposition of sodium aluminate solutions, and the resolution ratio and the last resolution ratio directly affect the output and quality of product. It is such a long time-delay and complex industrial process, which exits much uncertainty and is too complicated to describe with mathematical models, that it can not be controlled properly by traditional methods. In this paper, aimed to control optimal resolution ratio and the last decomposition ratio, the intelligent control system for continual carbonation decomposition process of sodium aluminate solutions is exploited which combined expert control with predictive control strategy. The principle knowledge and experts' experience of continuous carbonation decomposition process of sodium aluminate solutions is analysed and applied to design a expert control model. And a neural network predicting model is set up to forecast the next output of system which compensated the output of expert control model. Thus, the influence of long time-delay was conquered effectively and the process of continual carbonation decomposition was optimal controlled. The practical results show that eligible ratio of decomposition ratio increases by 4%, and average value of decomposition ratio increases by 0.95%. The system is always running well.
机译:在使用烧结过程的氧化铝生产中,使用铝酸钠解决方案的连续碳酸化分解方法和分辨率比和最后一个分辨率比例,是生产Al(OH) 3 的关键方法之一直接影响产品的输出和质量。这是一种很长的时滞和复杂的工业过程,其出现了很大的不确定性,并且对于用数学模型描述太复杂,而且通过传统方法无法正确控制它。本文旨在控制最佳分辨率和最后的分解比,利用铝制酸钠解决方案的持续碳化分解过程的智能控制系统,其具有预测控制策略的专家控制。分析了铝制酸钠解决方案连续碳化分解过程的原理知识和专家经验,设计了专家控制模型。和神经网络预测模型设置为预测系统的下一个输出,该输出补偿专家控制模型的输出。因此,有效地征服了长时间延迟的影响,并且不断碳化分解的过程是最佳的控制。实际结果表明,符合条件的分解比的比例增加了4%,分解比的平均值增加0.95%。系统始终运行良好。

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