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A Data-Driven Method for SKR Identification and Application to Stability Margin Estimation

机译:用于SKR识别和应用于稳定性边缘估计的数据驱动方法

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This paper proposes a new method to estimate the stability margin of a system by factorizing it into system's data-driven stable kernel representation (SKR) and controller's stable image representation (SIR). To this end, a coprime factorization technology is applied to the closed-loop system firstly. By analyzing the relations between the reference signal and internal signal, a new approach is adopted to calculate SKR of the system by the least square (LS) method. Furthermore, the data-driven realization of stability margin is calculated through system's SKR and controller's SIR. An example is given in the last part to testify the correctness of methodologies proposed in this paper.
机译:本文提出了一种通过将其分解为系统的数据驱动稳定的内核表示(SKR)和控制器的稳定图像表示(SIR)来提出一种新方法来估计系统的稳定裕度。为此,首先将协调分解技术应用于闭环系统。通过分析参考信号和内部信号之间的关系,采用了一种新方法来通过最小二乘(LS)方法计算系统的SKR。此外,通过系统的SKR和控制器的SIR计算稳定性边缘的数据驱动的实现。最后一部分给出了一个例子,以证明本文提出的方法的正确性。

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