A generalized projection estimation algorithm

IF 4.8 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Automatica Pub Date : 2024-10-02 DOI:10.1016/j.automatica.2024.111942

Patrizio Tomei, Riccardo Marino

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引用次数: 0

Abstract

Given a linear regression model in discrete-time containing a vector of

p

constant uncertain parameters, this paper addresses the problem of designing an exponentially convergent parameter estimation algorithm, even when the regressor vector is not persistently exciting (not even in a finite time interval). On the basis of the definition of lack of persistency of excitation of order

q

for the regressor vector,

0 \leq q \leq p

(which coincides with the classical definition of persistency of excitation when

q = 0

), a generalized projection estimation algorithm is proposed which guarantees global exponential convergence of the parameter estimation error and allows for the on-line computation of the order

q

of the lack of persistency of excitation. When the lack of persistency of excitation is of order zero, global exponential convergence to zero of the parameter estimation error is obtained, recovering a well-known result and the projection estimation algorithm as a special case.

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通用投影估算算法

给定一个离散时间线性回归模型，其中包含 p 个常数不确定参数矢量，本文要解决的问题是设计一种指数收敛的参数估计算法，即使在回归矢量没有持续激励（甚至在有限时间间隔内也没有）的情况下也是如此。根据对回归矢量的 q 阶缺乏持续激励的定义 0≤q≤p（这与 q=0 时激励持续性的经典定义相吻合），提出了一种广义投影估计算法，它能保证参数估计误差的全局指数收敛，并允许在线计算缺乏持续激励的 q 阶。当激励持续性不足的阶数为零时，参数估计误差会全局指数收敛为零，这恢复了一个众所周知的结果，投影估计算法是一个特例。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Automatica 工程技术-工程：电子与电气

CiteScore

10.70

自引率

7.80%

发文量

617

审稿时长

5 months

期刊介绍： Automatica is a leading archival publication in the field of systems and control. The field encompasses today a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. Since its inception in 1963, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field. After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. It features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience. Automatica solicits original high-quality contributions in all the categories listed above, and in all areas of systems and control interpreted in a broad sense and evolving constantly. They may be submitted directly to a subject editor or to the Editor-in-Chief if not sure about the subject area. Editorial procedures in place assure careful, fair, and prompt handling of all submitted articles. Accepted papers appear in the journal in the shortest time feasible given production time constraints.