排序方式: 共有227条查询结果,搜索用时 15 毫秒
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大规模变工况流程模拟的回溯同伦法 总被引:1,自引:0,他引:1
针对大规模变工况流程模拟中初值要求高、收敛性差的问题,提出了一种结合同伦思想与回溯搜索方法的回溯同伦法(HBM).该方法利用工况变量作为同伦参数,提高了同伦辅助问题的可解性.采用回溯法自动搜索同伦参数并作为非线性方程组求解器的外壳,降低了求解器对初值的要求.在Aspen Plus中将回溯同伦法与内部求解算法结合对乙烯分离过程变工况算例进行了模拟,结果表明HBM能够扩大收敛范围,可有效达到问题的物理边界.同时,使用回溯法搜索工况参数能保证找到同伦工况点,帮助分析过程瓶颈. 相似文献
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集散网络结构的PLC控制系统在生活饮用水深度处理中的应用 总被引:3,自引:0,他引:3
根据饮用水处理过程的特点和对控制的要求,设计并实现了基于PLC网络结构的二级集散控制系统,对该系统的特点作了介绍. 相似文献
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对BRC-100型余氯控制器的硬件结构和所采用的控制算法进行了介绍,并对所采用的基于ISA总线的CPU主板与6963LCM(160×128)点阵液晶的硬件和软件接口进行了研究,并且给出了该接口的显示驱动程序. 相似文献
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Dynamic principal component analysis (DPCA) is an extension of conventional principal component analysis (PCA) for dealing with multivariate dynamic data serially correlated in time. Based on the fact that the measured variables in relation to chunk monitoring of the industrial fluidized-bed reactor are highly cross-correlated and auto-correlated, this paper presents a practical strategy for chunk monitoring by adopting DPCA in order to overcome the shortcomings of the conventional method. After introducing the basic principle of DPCA, both how to determine the time lagged length of data matrix and how to calculate the nonparametric control limits when the dynamic data are not subject to the assumption of independently identically distribution (IID) were discussed. An appropriate DPCA model based on the real data from a industrial fluidized-bed reactor was built, with parallel analysis and empirical reference distribution (ERD) method to select time lagged length and control limits, respectively. During data pretreatment, data smoothing was used to reduce noise and the serial correlations to some degree. The simulation test results showed the effectiveness of the DPCA based method. 相似文献
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非线性离散时间系统的自适应函数观测器 总被引:2,自引:0,他引:2
针对一大类非线性离散时间系统提出了一种自适应函数观测器(AFO)。通过引入状态变换,得到了一类降阶形式的状态估计问题。采用一种稍加修改的强跟踪滤波算法估计降阶状态向量,然后利用降阶状态向量估计非线性状态函数。给出了AFO局部渐近收敛的充分条件。数值仿真示例显示AFO是一种具有强跟踪性质的自适应观测器,能在估计非线性状态函数的同时准确估计未知时变参数。 相似文献
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