双线性系统稳态模型的可辨识性分析
Analysis of Identifiability for Steady-State Models of Bilinear Systems
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摘要: 双线性模型描述的工业过程的稳态优化控制的稳态模型的建立,是利用优化过程中设定点的阶跃信号作为辨识的输入信息,以获取其稳态模型的强一致性估计,该辨识方法是在Fi为可逆的矩阵的假设下进行的,该文就Fi是否可逆进行了研究,并给出了双线性模型描述的系统可辨识的充分条件。Abstract: The foundation of Steady-State models for optimizing control of steady-state industrial processes which are described by bilinear models uses the step signals of steady-state as input identification signals in the course of optimizing control and obtain the strong consistency estimations of steady-state models. But only under the hypothesis of the Fi is reversible matrix, the identification technique is used. In the paper, the reversibility of Fi is studied and the sufficient conditions for system identifiability are given.