Interval observer design for unobservable switched nonlinear partial differential equation systems and its application

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-07-23 DOI:10.1002/rnc.7553
Xiaona Song, Zenglong Peng, Shuai Song, Vladimir Stojanovic
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Abstract

This paper designs an interval observer for switched nonlinear partial differential equation (PDE) systems. Initially, persistent dwell-time switching rules are used to model switched PDE systems with fast and slow switching phenomena. Next, for unobservable systems caused by uncertainties, the interval observer for the target PDE systems is proposed by utilizing unknown but bounded information of the initial states, boundary conditions, external disturbances, and measurement noises. Subsequently, by utilizing the estimated state's upper and lower bounds, an interval observer-based control strategy is devised to stabilize the studied systems, and sufficient conditions to ensure the stability of the target systems and the observation error dynamics are provided. Furthermore, the designed interval observer is employed to detect sensor failures in the presence of various uncertainties. Finally, two examples, including the lithium-ion battery's temperature estimation and fault detection, are utilized to demonstrate the effectiveness of the obtained methods.

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不可观测开关非线性偏微分方程系统的区间观测器设计及其应用
摘要 本文为开关非线性偏微分方程(PDE)系统设计了一种区间观测器。首先,使用持续停留时间切换规则来模拟具有快速和慢速切换现象的切换式 PDE 系统。接着,针对由不确定性引起的不可观测系统,利用初始状态、边界条件、外部干扰和测量噪声等未知但有界的信息,提出了目标 PDE 系统的区间观测器。随后,利用估计状态的上界和下界,设计了一种基于区间观测器的控制策略来稳定所研究的系统,并提供了确保目标系统稳定性和观测误差动态的充分条件。此外,还利用所设计的区间观测器来检测存在各种不确定性的传感器故障。最后,利用锂离子电池的温度估计和故障检测等两个实例来证明所获方法的有效性。
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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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Issue Information Disturbance observer based adaptive predefined-time sliding mode control for robot manipulators with uncertainties and disturbances Issue Information Issue Information A stabilizing reinforcement learning approach for sampled systems with partially unknown models
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