On the Stability Verification of Adaptive Uncertain and Coupled Dynamical Discrete-Time Systems

IF 3.8 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Adaptive Control and Signal Processing Pub Date : 2024-12-14 DOI:10.1002/acs.3954
Atahan Kurttisi, Islam A. Aly, K. Merve Dogan
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Abstract

In the controlled uncertain coupled dynamical systems employing standard model reference adaptive methods, stability is guaranteed either under minimally coupled dynamics or negligible system uncertainties. Thus, significant uncertainties and coupled dynamics in an uncertain system can lead to instability. In recent papers, continuous-time adaptive architectures are derived to compensate for uncertainties and coupled dynamics together. However, discretizing such algorithms doesn't guarantee the stability of the system directly since it complicates the Lyapunov analysis in discrete-time. This makes it challenging to generalize successful continuous-time adaptive control results to discrete-time environments. Thus, this article includes the stability verification for adaptive uncertain and coupled dynamical discrete-time systems and shows the efficacy of the novel controller over the standard ones through two illustrative examples.

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自适应不确定耦合动态离散系统的稳定性验证
采用标准模型参考自适应方法控制的不确定耦合动力系统,无论是在最小耦合动力学条件下,还是在可忽略的系统不确定性条件下,都能保证系统的稳定性。因此,不确定系统中显著的不确定性和耦合动力学会导致不稳定。在最近的论文中,导出了连续时间自适应结构来补偿不确定性和耦合动力学。然而,离散化这种算法并不能直接保证系统的稳定性,因为它使离散时间的李雅普诺夫分析变得复杂。这使得将成功的连续时间自适应控制结果推广到离散时间环境具有挑战性。因此,本文包括自适应不确定和耦合动态离散系统的稳定性验证,并通过两个示例说明了该控制器优于标准控制器的有效性。
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来源期刊
CiteScore
5.30
自引率
16.10%
发文量
163
审稿时长
5 months
期刊介绍: The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.
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