On the Identification of Self-Adjoint Linear Time-Varying State Models

P. Rapisarda

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On the Identification of Self-Adjoint Linear Time-Varying State Models

机译：关于自伴线性时变状态模型的识别

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A novel approach to the identification of linear time-varying (LTV) systems is illustrated, based on the concept of duality. Generically, if N input-output trajectories (uk, yk), k = 1,...,N of a self-adjoint LTV system are known, then the duality relation can be used to derive state trajectories xk, k = 1, . . ., N corresponding to such data. Such state trajectories are computed by factorizing a matrix directly constructed from input-output data of the primal and the dual system. From such input-state-output trajectories an “unfalsified” linear time-varying model can be obtained solving a system of functional equations.

机译：基于二元性的概念，示出了一种用于识别线性时变（LTV）系统的新方法。易于，如果是N个输入输出轨迹（UK，YK），k = 1，...，k = 1，...，k = 1，...，n的自伴随LTV系统是已知的，那么二元关系可用于导出状态轨迹XK，K = 1，。。。，n对应这些数据。通过根据原始和双系统的输入输出数据直接构建的矩阵来计算这种状态轨迹。从这种输入 - 状态输出轨迹可以求解功能方程的系统，可以获得“不突出的”线性时变模型。

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《IFAC PapersOnLine》 |2018年第15期|共6页
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P. Rapisarda;
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System identificationlinear time-varying systemsbehavioral system theory;

机译：系统判定线性时变量系统何种系统理论;

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On the Identification of Self-Adjoint Linear Time-Varying State Models

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