利用带记忆的估计实现鲁棒性识别和自适应控制的宽松激励条件

IF 2.2 2区 数学 Q2 AUTOMATION & CONTROL SYSTEMS SIAM Journal on Control and Optimization Pub Date : 2024-01-03 DOI:10.1137/22m1506183
Javier Gallegos, Norelys Aguila-Camacho
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引用次数: 0

摘要

SIAM 控制与优化期刊》第 62 卷第 1 期第 1-21 页,2024 年 2 月。 摘要本文设计了自适应控制器来跟踪线性和非线性系统的给定轨迹。除了连续性和有界性之外,跟踪轨迹不需要其他条件,就能同时确保指数收敛到跟踪参考、指数收敛到工厂识别以及对非参数不确定性的鲁棒性。为实现这一目标,我们提出了与自适应方案识别部分相关的激励条件,而不采用闭环信号,从而允许使用参考的瞬态增益。通过对近期文献中发现的几种使用记忆机制的估算算法进行概括,使用宽松的识别要求减弱了这种瞬态修改的影响。因此,在使用所提出的方案时,不需要跟踪轨迹的频谱内容--自适应理论中的经典要求--来保证上述特征。本文给出了一个数值示例,以说明所涉及的设计问题以及所提策略的显著特点。
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Relaxed Excitation Conditions for Robust Identification and Adaptive Control Using Estimation with Memory
SIAM Journal on Control and Optimization, Volume 62, Issue 1, Page 1-21, February 2024.
Abstract. In this paper, adaptive controllers are designed to track a given trajectory for linear and nonlinear systems. No condition on the tracked trajectory, other than continuity and boundedness, is needed to simultaneously ensure exponential convergence to the tracking reference, exponential convergence to the identification of the plant, and robustness to nonparametric uncertainties. To achieve this, the formulation of the excitation condition associated with the identification part of the adaptive scheme is proposed without employing closed-loop signals, allowing the use of a transient enrichment of the reference. The effect of this transient modification is attenuated by using relaxed requirements for the identification, obtained through a generalization of several estimation algorithms found in recent literature that use memory mechanisms. Consequently, no spectral content of the tracked trajectory—a classic requirement in adaptive theory—is needed to guarantee the mentioned features when the proposed scheme is used. A numerical example is given to illustrate the design aspects involved and the distinctive features of the proposed strategy.
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来源期刊
CiteScore
4.00
自引率
4.50%
发文量
143
审稿时长
12 months
期刊介绍: SIAM Journal on Control and Optimization (SICON) publishes original research articles on the mathematics and applications of control theory and certain parts of optimization theory. Papers considered for publication must be significant at both the mathematical level and the level of applications or potential applications. Papers containing mostly routine mathematics or those with no discernible connection to control and systems theory or optimization will not be considered for publication. From time to time, the journal will also publish authoritative surveys of important subject areas in control theory and optimization whose level of maturity permits a clear and unified exposition. The broad areas mentioned above are intended to encompass a wide range of mathematical techniques and scientific, engineering, economic, and industrial applications. These include stochastic and deterministic methods in control, estimation, and identification of systems; modeling and realization of complex control systems; the numerical analysis and related computational methodology of control processes and allied issues; and the development of mathematical theories and techniques that give new insights into old problems or provide the basis for further progress in control theory and optimization. Within the field of optimization, the journal focuses on the parts that are relevant to dynamic and control systems. Contributions to numerical methodology are also welcome in accordance with these aims, especially as related to large-scale problems and decomposition as well as to fundamental questions of convergence and approximation.
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