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Identification of continuous-time hybrid 'Box-Jenkins' systems with multiple unknown time delays using two-stage parameter estimation algorithm

机译:使用两阶段参数估计算法识别具有多个未知时延的连续时间混合“ Box-Jenkins”系统

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Purpose This study/paper aims to present a separable identification algorithm for a multiple input single output (MISO) continuous time (CT) hybrid "Box-Jenkins". Design/methodology/approach This paper proposes an optimal method for the identification of MISO CT hybrid "Box-Jenkins" systems with unknown time delays by using the two-stage recursive least-square (TS-RLS) identification algorithm. Findings The effectiveness of the proposed scheme is shown with application to a simulation example. Originality/value A two-stage recursive least-square identification method is developed for multiple input single output continuous time hybrid "Box-Jenkins" system with multiple unknown time delays from sampled data. The proposed technique allows the division of the global CT hybrid "Box-Jenkins" system into two fictitious subsystems: the first one contains the parameters of the system model, including the multiple unknown time delays, and the second contains the parameters of the noise model. Then the TS-RLS identification algorithm can be applied easily to estimate all the parameters of the studied system.
机译:目的本研究/论文旨在为多输入单输出(MISO)连续时间(CT)混合“ Box-Jenkins”提出一种可分离的识别算法。设计/方法/方法本文提出了一种通过使用两阶段递归最小二乘(TS-RLS)识别算法来识别未知延迟的MISO CT混合“ Box-Jenkins”系统的最佳方法。结论将所提出的方案的有效性应用于仿真示例。独创性/值针对具有多个未知时间延迟的多输入单输出连续时间混合“ Box-Jenkins”系统,开发了一种两阶段递归最小二乘识别方法。所提出的技术允许将全局CT混合“ Box-Jenkins”系统划分为两个虚拟子系统:第一个子系统包含系统模型的参数,包括多个未知时延,第二个子系统包含参数的模型。噪声模型。然后,可以轻松地将TS-RLS识别算法应用于估计所研究系统的所有参数。

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