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多变量热工系统模型辨识方法研究
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摘要
本文主要工作分两部分,第一部分推导出机组协调控制系统机理模型,并且通过基于遗传算法对机理模型参数进行辨识研究。根据单元机组的低阶非线性模型,推导出一个双输入双输出、能够描述机组动态特性及机炉间相互耦合关系的协调控制系统传递函数矩阵。依此模型为基础,提出一种基于改进的遗传算法的参数辨识方法。第二部分针对某600MW单元机组的实际闭环运行数据,进行数据预处理,将单元机组协调系统合理简化为一个双输入双输出的多变量对象模型。并将模型分解为子模型再进一步分解为子子模型,使用基于增广最小二乘和辅助变量辨识算法,估计出整个模型的结构和参数,得到一组线性数学模型。
Paper is composed of two parts,The first part is derived coordinated control system model of the mechanism, and the model parameters is identified through the mechanism of genetic algorithm. The model of coordinated control system can capture the essential dynamics of a unit so it is typical for the process.Based on this model and applyingthe model,an parameter identification algorithm based on the improved genetic algorithm is proposed.The second part utilized a set of actual close-loop running data from a 600MW unit. A lot of work was done on dealing the data. After that the unitcoordinated control system was simplified into a set of two-input andtwo-output multi variable object models for each equilibrium point. The model was then decomposed into submodels. through the same method,subsubmodels were gained. by Extend_LS_Identify and Auxiliary variable recursive algorithm,the models structure and parameters were obtained,and a set of mathematical models linear is gained.
引文
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