引用本文:陈庆新,万百五.利用工业大系统动态信息建立稳态模型及其强一致性分析[J].控制理论与应用,1993,10(5):508~515.[点击复制]
CHEN Qingxin and WAN Baiwu.Steady-State Establishment of the Large-Scale Industrial Process by Use of the Dynamic Information and Its Strong Consistency Analysis[J].Control Theory and Technology,1993,10(5):508~515.[点击复制]
利用工业大系统动态信息建立稳态模型及其强一致性分析
Steady-State Establishment of the Large-Scale Industrial Process by Use of the Dynamic Information and Its Strong Consistency Analysis
摘要点击 787  全文点击 400  投稿时间:1991-07-01  修订日期:1993-03-13
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DOI编号  
  1993,10(5):508-515
中文关键词  系统辨识  大系统  递阶辨识  稳态模型
英文关键词  systems identification  large-scale system  hierarchial identification  steady-state model
基金项目  
作者单位
陈庆新,万百五 西安交通大学系统工程研究所 
中文摘要
      本文提出了一种在相当弱的条件下,仅仅利用优化过程中系统设定点例行阶跃变化作为激励信号,对各子系统并行使用简单最小二乘法和近似动态线性模型,充分运用大系统的动态信息,得到了大系统稳态模型的一致估计的理论证明,并利用数字仿真进一步验证了其方法的有效性。还给出了一种实用的,能强一致估计线性渐近定常大系统稳态模型的方法。
英文摘要
      In this paper, under the weak assumptions such as only the step changes of system set points being the exciting signal, unknown structures and the dynamic parameters, approximate linear dynamic model and the least squares estimation method, for the linear slow time-varying large-scale system, the steady-state gain estimate is formed from the estimate and the convergence of the parallel iteration are analyzed. Based on this consistency theorem, a pragmatic method to get the strong consistent estimate of the steady-state model of the large-scale system is presented. Simulation study has already proved this point.