首页> 外文会议>Proceedings of the Fifth symposium on fractional differentiation and its applications >Higher-Order Statistics-based methods for order and parameter estimation of continuous-time errors-in-variables fractional models
【24h】

Higher-Order Statistics-based methods for order and parameter estimation of continuous-time errors-in-variables fractional models

机译:基于高阶统计量的连续时间变量误差分数模型的阶数和参数估计方法

获取原文
获取原文并翻译 | 示例

摘要

This paper considers the problem of dynamic Errors-In-Variables identification by fractional model. First, differentiation orders are fixed and the differential equation coefficients are estimated using two estimators based on Higher-Order Statistics (third-order cumulants). Then, all differentiation orders are set as integer multiples of a commensurate order. The fractional third-order based least squares algorithm (ftocls) and the fractional third-order based iterative least squares algorithm (ftocils) are extended to estimate the commensurate order with a nonlinear optimization algorithm. A simulation example is used to demonstrate the performance of the proposed methods.
机译:本文考虑了用分数模型动态识别变量误差的问题。首先,微分阶数是固定的,并且使用基于高阶统计量(三阶累积量)的两个估计器来估计微分方程系数。然后,将所有微分阶数设置为相称阶数的整数倍。基于分数三阶的最小二乘算法(ftocls)和基于分数三阶的迭代最小二乘算法(ftocils)被扩展为使用非线性优化算法来估计相应的阶数。仿真例子用来说明所提出方法的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号