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Parameters and Fractional Differentiation Orders Estimation for Linear Continuous-Time Non-Commensurate Fractional Order Systems

机译:线性连续时间非公分数阶系统的参数和分数微分阶估计

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摘要

This paper proposes a two-stage estimation algorithm to solve the problem of joint estimation of the parameters and the fractional differentiation orders of a linear continuous-time fractional system with non-commensurate orders. The proposed algorithm combines the modulating functions and the first-order Newton methods. Sufficient conditions ensuring the convergence of the method are provided. An error analysis in the discrete case is performed. Moreover, the method is extended to the joint estimation of smooth unknown input and fractional differentiation orders. The performance of the proposed approach is illustrated with different numerical examples. Furthermore, a potential application of the algorithm is proposed which consists in the estimation of the differentiation orders of a fractional neurovascular model along with the neural activity considered as input for this model.
机译:提出了一种两阶段估计算法,以解决参数不连续估计和线性连续时间分数阶系统的微分阶数的联合估计问题。所提出的算法结合了调制函数和一阶牛顿法。提供了确保该方法收敛的充分条件。在离散情况下执行错误分析。此外,该方法扩展到平滑的未知输入和分数微分阶的联合估计。通过不同的数值示例说明了该方法的性能。此外,提出了该算法的潜在应用,该算法包括估计分数神经血管模型的分化阶数以及被视为该模型输入的神经活动。

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