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A modified method for closed-loop identification of transferfunction models

机译:一种改进的传递函数模型闭环辨识方法

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摘要

Substantial revisions on the newly proposed bias correction based method are made in the framework of indirect identification of a linear (possibly unstable) plant operating in closed loop with a low-order stabilizing controller. By making a new formulation of a least-squares estimate of an intermediate parameter vector purposely introduced, the modified algorithm is able to achieve a direct yet unbiased closed-loop system estimate in the presence of misspecified noise model. With no identification of a high-order augmented closed-loop system, the computational complexity of the algorithm is significantly reduced. Simulations of identifying an open-loop unstable plant illustrate the promising performance of the modified algorithm in low signal-to-noise ratio environments
机译:在间接识别使用低阶稳定控制器闭环运行的线性(可能不稳定)工厂的框架内,对新提出的基于偏差校正的方法进行了重大修订。通过有意引入中间参数矢量的最小二乘估计的新公式,在存在错误指定的噪声模型的情况下,改进的算法能够实现直接但无偏见的闭环系统估计。由于没有识别出高阶增强闭环系统,因此该算法的计算复杂度大大降低了。识别开环不稳定工厂的仿真说明了改进算法在低信噪比环境中的有希望的性能

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