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Multi-innovation based Identification of Output Error Model with Time Delay under Load Disturbance

机译：负载干扰下的输出误差模型的多创新识别

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摘要

In this paper, a robust output error model identification method is proposed for industrial processes with time delay subject to load disturbance. By viewing the load disturbance response as a time-variant parameter to be estimated, an extended recursive least-squares (RLS) identification method is established to simultaneously estimate the model parameters and the disturbance response, based on a multi-innovation fitting strategy. The integer type time delay parameter is determined by using a one-dimensional searching approach. An auxiliary model is used to estimate the noise-free output against stochastic noise. Besides, two adaptive forgetting factors are introduced to improve the convergence rates of estimating the time-invariant model parameters and the time-variant disturbance response, respectively. The effectiveness and merit of the proposed method is demonstrated by an illustrative example.
机译：本文提出了一种强大的输出误差模型识别方法，用于工业过程，其延迟受负载干扰。通过将负载扰动响应视为待估计的时间变量参数，建立了扩展的递归最小二乘（RLS）识别方法以同时估计基于多创新拟合策略的模型参数和干扰响应。通过使用一维搜索方法来确定整数型时间延迟参数。辅助模型用于估计随机噪声的无噪声输出。此外，引入了两个自适应遗忘因子，以改善估计时间不变模型参数和时变扰动响应的收敛速率。通过说明性示例对所提出的方法的有效性和优异。

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