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Subsystem identification of multivariable feedback and feedforward systems

机译:多变量反馈和前馈系统的子系统识别

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摘要

We present a frequency-domain technique for identifying multivariable feedback and feedforward subsystems that are interconnected with a known subsystem. This subsystem identification algorithm uses closed-loop input-output data, but no other system signals are assumed to be measured. In particular, neither the feedback signal nor the outputs of the unknown subsystems are assumed to be measured. We use a candidate-pool approach to identify the feedback and feedforward transfer function matrices, while guaranteeing asymptotic stability of the identified closed-loop transfer function matrix. The main analytic result shows that if the data noise is sufficiently small and the candidate pool is sufficiently dense, then the parameters of the identified feedback and feedforward transfer function matrices are arbitrarily close to the true parameters. (C) 2016 Elsevier Ltd. All rights reserved.
机译:我们提出了一种频域技术,用于识别与已知子系统互连的多变量反馈和前馈子系统。该子系统识别算法使用闭环输入输出数据,但假定没有其他系统信号被测量。特别是,既不测量反馈信号也不知道未知子系统的输出。我们使用候选池方法来识别反馈和前馈传递函数矩阵,同时保证所识别的闭环传递函数矩阵的渐近稳定性。主要分析结果表明,如果数据噪声足够小且候选池足够密集,则所标识的反馈和前馈传递函数矩阵的参数将任意接近真实参数。 (C)2016 Elsevier Ltd.保留所有权利。

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