利用新型预定义时间稳定性准则对具有滞后非线性的开关非线性系统进行自适应量化跟踪控制

IF 3.9 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Ling Jin, Lei Su, Shaoyu Lü, Kang Wang, Jing Wang
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引用次数: 0

摘要

本文研究了具有输入量化和滞后非线性的开关非线性系统的自适应跟踪控制问题。首先,考虑了滞后非线性现象,并采用 Bouc-Wen 滞后模型来解决控制器设计的复杂性。考虑到时间采样机制可能导致通信资源的浪费,引入了滞后量化器来解决这一问题。此外,还构建了一个指令滤波器,以缓解反步进过程中遇到的复杂性爆炸问题。随后,与传统的预定义时间 Lemma 相比,提出了一种新型预定义时间 Lemma,即使预定义时间参数已确定,它也能有效地调整系统性能。在这种情况下,考虑到滞后特性和输入量化,通过应用反向步法设计了一种新型自适应预定义时间控制方案,该方案可以在预定义时间框架内跟踪参考信号。最后,通过数值和实际例子阐述了所提策略的灵活性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive quantized tracking control for switched nonlinear systems with hysteresis nonlinearity using a novel predefined-time stability criterion

This article investigates the adaptive tracking control problem for switched nonlinear systems with input quantization and hysteresis nonlinearity. First, the hysteresis nonlinear phenomenon is considered and the Bouc–Wen hysteresis model is employed to address the complexities of controller design. Considering the time-sampling mechanism may lead to the wastage of communication resources, a hysteresis quantizer is introduced to address this issue. Additionally, a command filter is constructed to relieve complexity explosion issues encountered during the backstepping process. Subsequently, compared with the conventional predefined-time lemma, a novel predefined-time lemma is proposed which can effectively adjust system performance even if the predefined-time parameter is determined. In this case, a novel adaptive predefined-time control scheme is devised by considering hysteresis properties and input quantization via the application of backstepping, which can track the reference signals within the predefined-time frame. Finally, the flexibility and effectiveness of the proposed strategy are elaborated through numerical and practical examples.

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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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