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Recursive subspace identification of Hammerstein-type nonlinear systems under slow time-varying load disturbance

机译:慢时变负载扰动下的Hammerstein型非线性系统的递归子空间辨识

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In this paper, a recursive subspace identification method is proposed for Hammerstein-type nonlinear systems that is affected by slow time-varying load disturbance. Based on superposition principle, the system output response is divided into three parts, i.e. disturbed, stochastic and deterministic components. Correspondingly, the disturbance response is regarded as a time-varying variable to be identified. In order to achieve the goal of identifying the system matrices accurately, a recursive leastsquares (RLS) identification method is proposed. The peculiarity of this method lies in the introduction of forgetting factors. One of the forgetting factors quickly tracks the load disturbance response, the other are for recursive estimation. An illustrative example is presented to demonstrate the effectiveness and merit of the proposed identification method.
机译:提出了一种受时变缓慢的负载扰动影响的Hammerstein型非线性系统的递归子空间辨识方法。根据叠加原理,系统输出响应分为三个部分,即干扰,随机和确定性分量。相应地,扰动响应被视为待识别的随时间变化的变量。为了达到准确识别系统矩阵的目的,提出了一种递推最小二乘(RLS)识别方法。这种方法的独特之处在于遗忘因素的引入。遗忘因素之一是快速跟踪负载扰动响应的,另一因素是递归估计的。给出了一个说明性的例子,以证明所提出的识别方法的有效性和优点。

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