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Closed-loop subspace-based identification algorithm using third-order cumulants

机译:基于三阶累积量的基于闭环子空间的识别算法

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摘要

The problem of closed-loop system identification for coloured noise system without any knowledge of feedback controller is considered. We develop a solution to this problem in the framework of subspace identification based on high-order cumulants. The key of the developed algorithm is using the properties that the third-order cumulants are insensitive to any coloured Gaussian noises. By post-multiplying a suitable instrumental variable to the noise terms, the cross third-order cumulants are constructed that become zero when the noises are Gaussian distributed, and meanwhile the column rank of extended observability matrix is maintained. Thus, the standard subspace identification algorithms can be extended to closed-loop system corrupted by arbitrary coloured noises. A numerical simulation is presented to demonstrate the proposed algorithm.
机译:考虑了没有反馈控制器知识的有色噪声系统闭环系统辨识问题。我们在基于高阶累积量的子空间识别框架中开发了针对此问题的解决方案。该算法的关键是利用三阶累积量对任何有色高斯噪声不敏感的特性。通过将合适的工具变量乘以噪声项,可以构建交叉的三阶累积量,当噪声为高斯分布时,交叉的三阶累积量变为零,同时保持扩展的可观察性矩阵的列秩。因此,标准子空间识别算法可以扩展到被任意彩色噪声破坏的闭环系统。数值仿真表明了该算法的有效性。

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