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An improved algebraic geometric solution to the identification of switched ARX models with noise

机译:一种改进的代数几何解决方案,用于识别带噪声的切换ARX模型

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In this paper, we present an improved algebraic geometry solution for the identification of switched ARX models in the presence of measurement noise. The procedure utilizes the highest order of sub-models, which is estimated by using statistical analysis of effective singular values in matrix rank determination. After embedding sub-models into a large continuous-time model for omitting the necessity of switching sequence, an analytical solution for the two-mode system is obtained using matrix differential calculus. The improvements made to the previous method are verified by simulations on two linear systems. Also the effectiveness of the proposed method is shown by using a two mode experimental pilot plant.
机译:在本文中,我们提出了一种改进的代数几何解决方案,用于在存在测量噪声的情况下识别切换的ARX模型。该过程利用子模型的最高顺序,该顺序通过对矩阵秩确定中的有效奇异值进行统计分析来估计。将子模型嵌入到大的连续时间模型中以省去切换顺序的必要性之后,使用矩阵微分算法获得了双模系统的解析解。通过对两个线性系统的仿真,验证了对先前方法的改进。通过使用两模式实验中试装置,还表明了所提出方法的有效性。

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