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Optimal experiment design for identification of ARX models with constrained output in non-Gaussian noise

机译：非高斯噪声下约束输出的ARX模型辨识的优化实验设计

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摘要

The identification of ARX models with constrained output variance in the presence of non-Gaussian distribution of measurements is proposed in this paper. In the presence of non-Gaussian noise, the Masreliez-Martin filter (robust Kalman filter) is the natural frame for identification of model parameters. For the purpose of increasing the practical value of the filter, a heuristic modification is performed. Also, an optimal input is obtained by a minimum variance controller with a Gaussian reference signal. A fundamental issue in experiment design is that the optimal input in general depends on system parameters to be estimated. In order to realize obtained optimal input, authors have proposed a two-stage adaptive procedure, where one iterates between parameter estimation, on the one side, and experiment design using the current parameter estimates, on the other. The practical behavior of new approach to optimal input design for robust identification of ARX models is shown by intensive simulations.
机译：本文提出了在存在非高斯分布的测量情况下，在输出方差受限的情况下识别ARX模型的方法。在存在非高斯噪声的情况下，Masreliez-Martin滤波器（鲁棒的Kalman滤波器）是识别模型参数的自然框架。为了增加滤波器的实用价值，进行启发式修改。另外，最小方差控制器利用高斯参考信号获得最佳输入。实验设计中的一个基本问题是，最佳输入通常取决于要估计的系统参数。为了实现获得的最佳输入，作者提出了一个两阶段的自适应程序，其中一方面在参数估计和使用当前参数估计的实验设计之间进行迭代。深入的仿真显示了用于优化输入设计以稳健识别ARX模型的新方法的实际行为。

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  • 来源
    《Applied Mathematical Modelling》 |2016年第14期|6676-6689|共14页
  • 作者

    Vladimir Stojanovic; Novak Nedic; Dragan Prsic; Ljubisa Dubonjic;

  • 作者单位

    Department of Automatic Control, Robotics and Fluid Technique, Faculty of Mechanical and Civil Engineering in Kraljevo, University of Kragujevac, Dositejeva 19, 36000 Kraljevo, Serbia;

    Department of Automatic Control, Robotics and Fluid Technique, Faculty of Mechanical and Civil Engineering in Kraljevo, University of Kragujevac, Dositejeva 19, 36000 Kraljevo, Serbia;

    Department of Automatic Control, Robotics and Fluid Technique, Faculty of Mechanical and Civil Engineering in Kraljevo, University of Kragujevac, Dositejeva 19, 36000 Kraljevo, Serbia;

    Department of Automatic Control, Robotics and Fluid Technique, Faculty of Mechanical and Civil Engineering in Kraljevo, University of Kragujevac, Dositejeva 19, 36000 Kraljevo, Serbia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Optimal experiment design; Two-stage adaptive procedure; ARX model; Constrained output; Robust identification;

    机译：优化实验设计;两阶段自适应程序;ARX模型;输出受限;稳健的识别;

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