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改进的催化裂化集总动力学参数估计方法 总被引:1,自引:0,他引:1
针对催化裂化复杂反应体系 ,提出了一种在NLJ算法基础上改进的随机搜索优化算法NLJ ,该方法引入了优化的中间结果和目标函数的变化来修正搜索范围 ,从而减少了搜索的随机性。该方法应用于催化裂化十集总动力学模型轻循环油反应网络动力学参数估计 ,降低了搜索算法对初值和实验误差的要求 ,保证了收敛稳定性。 相似文献
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A self-organizing radial basis function(RBF) neural network(SODM-RBFNN) was presented for predicting the production yields and operating optimization. Gradient descent algorithm was used to optimize the widths of RBF neural network with the initial parameters obtained by k-means learning method. During the iteration procedure of the algorithm, the centers of the neural network were optimized by using the gradient method with these optimized width values. The computational efficiency was maintained by using the multi-threading technique. SODM-RBFNN consists of two RBF neural network models: one is a running model used to predict the product yields of fluid catalytic cracking unit(FCCU) and optimize its operating parameters; the other is a learning model applied to construct or correct a RBF neural network. The running model can be updated by the learning model according to an accuracy criterion. The simulation results of a five-lump kinetic model exhibit its accuracy and generalization capabilities, and practical application in FCCU illustrates its effectiveness. 相似文献
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The accurate model is the most important and basic condition for the application of advanced process control, but the conventional methods do not provide satisfactory results in the case of unstable processes. To effectively control these processes, a novel identification method (Model Parameters and Initial States Identification simultaneously in closed loop --MPISI) is proposed. The model parameters and initial states of state equation can be simultaneously identified using this method. The results of simulation and application show that this method has the advantageous of disturbance-rejection and robustness. This method proposes a novel way for the optimization and the advanced control of the process systems. 相似文献
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一种新型模糊液位控制及其应用 总被引:2,自引:0,他引:2
在连续生产过程中,工艺上通过设立缓冲容器来解决前后工序之间的物料量突变,以确保生产的平稳性,针对这类容器的液位控制,常规PID定值控制已满足不了上述要求。为解决这个问题,以长期现场实践为基础,根据操作人员的思维特性,提出了一种基于模糊控制和常规控制相结合的液位区域控制方法。该方法以液位的上下限和变化量作为输入模糊量化依据,改变了传统输入模糊量化方法,同时对于模糊输出量到控制输出采用新的转换方法,使模糊输出离散量转化为希望调节的液位量。为提高控制精确度,在实际控制输出与希望调节偏差较大时,增加了输出校正环节以减少输出误差。这种方法允许液位在给定的高低限范围内波动,以保证送出的物料缓慢平稳变化;只有液位超出高低限时,或液位在正常范围内,并且液位变化量超过给定阈值时才进行调节,以确保维持下游工序的负荷平稳。实际应用结果验证了这种方法的有效性。 相似文献
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针对乙烯装置裂解炉在开工、正常运行和负荷调整过程中各组炉管的出口温度存在不均衡的问题,以乙烷制乙烯裂解炉为研究对象,提出基于热量平衡的裂解炉支路温度及负荷控制方法。基于裂解炉多支路炉管的结构特性,需保持支路流量调整前后的热量平衡,以消除裂解炉支路温度偏差,稳定裂解炉出口温度(COT)。同时,加入负荷控制,协同调配各支路流量分配,消除负荷变化对温度的影响。以此为基础,在集散控制系统(DCS)上设计并开发了支路温度及负荷控制器,并应用于某石化公司0.60 Mt/a乙烷制乙烯装置的5台裂解炉,结果表明,该控制器可以不受负荷调整的影响,将COT波动范围精准控制在±0.5℃,支路温差波动范围控制在1℃内,减少了开工物料损失,保证了裂解炉的平稳运行。 相似文献
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