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Comment on: A robust observer based on the nonlinear descriptor systems application to estimate the state of charge of lithium-ion batteries 评论基于非线性描述子系统的鲁棒观测器在锂离子电池充电状态估算中的应用
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-23 DOI: 10.1016/j.jfranklin.2024.107287
Mohamed Zerrougui
In the paper by Meng et al. (2023), an observer is proposed for nonlinear singular systems. The authors claim that their method effectively handles nonlinearity and disturbances affecting both the dynamic and algebraic parts of the system. They compare the performance of their observer with that proposed by Darouach et al. (2011), focusing on observer design for nonlinear singular systems with disturbances affecting the dynamic and algebraic parts as well as the output of the system. Furthermore, this approach has been extended to several other classes of systems, as discussed in Zerrougui et al. (2014) [1], Darouach et al. (2013) [2], and Darouach et al. (2010) [3]. Meng et al. apply their observer to estimate the state of charge of a lithium battery in comparison with the results in Snoussi et al. (2020). In this note, we aim to highlight the discrepancies between our respective findings. Specifically, we explain that the observer proposed by Meng et al. (2023), is more restrictive and may not be suitable for singular systems with nonlinear algebraic components or disturbances affecting this part or affecting outputs. Additionally, Meng et al. (2023) revisit the framework introduced in Darouach et al. (2011), adding a particular form for the matrix Φ that renders it more restrictive, without any contribution in the stability synthesis part.
Meng 等人 (2023) 的论文提出了一种非线性奇异系统观测器。作者称他们的方法能有效处理影响系统动态和代数部分的非线性和干扰。他们将其观测器的性能与 Darouach 等人(2011 年)提出的观测器的性能进行了比较,重点关注非线性奇异系统的观测器设计,该系统的动态和代数部分以及输出都会受到干扰。此外,这种方法还扩展到了其他几类系统,如 Zerrougui 等人(2014)[1]、Darouach 等人(2013)[2] 和 Darouach 等人(2010)[3] 所讨论的那样。与 Snoussi 等人(2020 年)的研究结果相比,Meng 等人利用他们的观测器估算了锂电池的电荷状态。在本说明中,我们旨在强调我们各自研究结果之间的差异。具体来说,我们解释说,Meng 等人(2023 年)提出的观测器限制性更强,可能不适合具有非线性代数成分或干扰影响这部分或影响输出的奇异系统。此外,Meng 等人(2023 年)重新审视了 Darouach 等人(2011 年)提出的框架,为矩阵 Φ 增加了一种特殊形式,使其更具限制性,但对稳定性合成部分没有任何贡献。
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引用次数: 0
Novel discretized gravitational search algorithm for effective medical hyperspectral band selection 用于有效选择医疗高光谱波段的新型离散重力搜索算法
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-23 DOI: 10.1016/j.jfranklin.2024.107269
Chenglong Zhang , Xiaopeng Ma , Aizhu Zhang , Bin Yan , Kai Zhao , Qiyuan Cheng
Medical hyperspectral imaging present a promising avenue for non-invasive diagnostic methods for diseases. Nonetheless, the sparsity of medical hyperspectral data within high-dimensional spaces introduces the “curse of dimensionality”, which diminishes the efficiency and accuracy of data processing efforts. Therefore, spectral dimensionality reduction emerges as an essential process in the analysis and utilization of MHSIs data. To retain the intrinsic properties of the spectral bands, an effective unsupervised band selection algorithm is proposed leveraging the gravitational search algorithm (GSA-UBS) to identify the optimal band subset. Taking into account the informational content and redundancy among candidate bands, a comprehensive evaluation criterion is established that incorporates a band distance matrix and an information entropy vector. Additionally, a straightforward discrete search strategy is developed that enables gravitational search algorithm to directly retrieve the original sequence numbers of the selected bands, bypassing the conventional 0–1 band weighting approach. The extensive evaluation of GSA-UBS on three publicly available invivo brain cancer MHSIs datasets and a remote sensing hyperspectral image demonstrates its superior performance compared to various state-of-the-art methods. The source code for GSA-UBS can be accessed at https://github.com/zhangchenglong1116/GSA_UBS.
医学高光谱成像为疾病的非侵入性诊断方法提供了一个前景广阔的途径。然而,医学高光谱数据在高维空间中的稀疏性带来了 "维度诅咒",降低了数据处理工作的效率和准确性。因此,光谱降维成为分析和利用 MHSIs 数据的重要过程。为了保留光谱波段的固有特性,利用引力搜索算法(GSA-UBS)提出了一种有效的无监督波段选择算法,以确定最佳波段子集。考虑到候选波段之间的信息含量和冗余度,建立了一个包含波段距离矩阵和信息熵向量的综合评价标准。此外,还开发了一种直接的离散搜索策略,使引力搜索算法能够绕过传统的 0-1 波段加权方法,直接检索所选波段的原始序列号。GSA-UBS 在三个公开的活体脑癌 MHSIs 数据集和一幅遥感高光谱图像上进行了广泛的评估,证明其性能优于各种最先进的方法。GSA-UBS 的源代码可通过 https://github.com/zhangchenglong1116/GSA_UBS 访问。
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引用次数: 0
Data-driven integral sliding mode predictive control with optimal disturbance observer 具有最佳干扰观测器的数据驱动积分滑动模式预测控制
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-23 DOI: 10.1016/j.jfranklin.2024.107278
Rui Xia , Xiaohang Song , Dawei Zhang , Dongya Zhao , Sarah K. Spurgeon
In this paper, a novel data-driven integral sliding mode predictive control algorithm based on an optimal disturbance observer (DDISMPC-ODO) is proposed for a class of nonlinear discrete-time systems (NDTS) subject to external disturbances. The designed optimal disturbance observer realizes the precise observation of the lumped disturbance, thus ameliorating the accuracy of the controller and weakening problems with chattering. In this work, a robust pseudo-partial derivative (PPD) estimation algorithm is introduced, which not only improves the system performance, but also facilitates theoretical proof of parameter estimation and tracking accuracy. The convergence of the PPD estimation error and disturbance observation error is proved. It is also proved that the accuracy of the disturbance observation error can converge to O(T3) and then the magnitude of the sliding variable and the tracking error are also reduced to O(T3) respectively. Finally, the effectiveness of the proposed method is demonstrated by a simulation example and an experiment.
本文针对一类受外部扰动影响的非线性离散时间系统(NDTS),提出了一种基于最优扰动观测器的新型数据驱动积分滑模预测控制算法(DDISMPC-ODO)。所设计的最优扰动观测器实现了对块状扰动的精确观测,从而提高了控制器的精度并削弱了颤振问题。本研究引入了一种鲁棒伪偏导数(PPD)估计算法,不仅提高了系统性能,而且有助于参数估计和跟踪精度的理论证明。证明了 PPD 估计误差和扰动观测误差的收敛性。同时证明了扰动观测误差的精度可以收敛到 O(T3),然后滑动变量的大小和跟踪误差也分别减小到 O(T3)。最后,通过仿真实例和实验证明了所提方法的有效性。
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引用次数: 0
A cholera model coupling within-host and between-host with age-dependent and asymptomatic infections 霍乱模型将宿主内和宿主间与年龄依赖性和无症状感染耦合在一起
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-22 DOI: 10.1016/j.jfranklin.2024.107283
Ruixia Yin , Hao Wu , Long Zhang , Hong-Li Li , Yantao Luo , Zhidong Teng
In this paper, a coupling cholera epidemic model is proposed, in which the pathogens could both spread within-host and between-host, meanwhile, there exist age-dependent infection between the asymptomatic and symptomatic infected people. For the fast-time subsystem, the infection-free and endemic equilibria are both globally asymptotically stable. For the slow-time subsystem, the basic reproduction number R0 is determined, by which we observe that the disease-free equilibrium is globally asymptotically stable (the absence of pathogens in environment) if R0<1, while the endemic equilibrium is globally asymptotically stable (the presence of pathogens in environment) when R0>1. The theoretical results are illustrated by numerical simulations, by which we find that age-dependent and asymptomatic infections may further promote cholera spread. Besides, the linking of pathogen transmission at the individual level with infection at the population level could result in forward or backward bifurcation.
本文提出了一个耦合霍乱流行模型,其中病原体既可以在宿主内传播,也可以在宿主间传播,同时,无症状和有症状的感染者之间存在年龄依赖性感染。对于快时间子系统,无感染均衡和流行均衡都是全局渐近稳定的。通过数值模拟,我们发现年龄依赖性和无症状感染可能会进一步促进霍乱的传播。此外,个体层面的病原体传播与群体层面的感染之间的联系可能会导致向前或向后分叉。
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引用次数: 0
Rational-quadratic kernel-based maximum correntropy Kalman filter for the non-Gaussian noises 针对非高斯噪声的基于有理二次核的最大熵卡尔曼滤波器
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-21 DOI: 10.1016/j.jfranklin.2024.107286
Xuehua Zhao , Dejun Mu , Jiahui Yang , Jiahao Zhang
In this paper, a rational-quadratic kernel-based maximum correntropy Kalman filter (RKMCKF) algorithm is proposed to improve the estimation accuracy for non-Gaussian noise interference. Firstly, the RKMCKF algorithm is derived to eliminate the singular matrix produced by multi-dimensional non-Gaussian noise disturbance. Secondly, the upper limit is analyzed to provide a theoretical range for kernel bandwidth, which is beneficial for the selection of proper kernel bandwidths and boosting the precision of state estimation. Furthermore, the boundness of the state estimation error is verified to manifest the RKMCKF algorithm stability. Finally, under different types of non-Gaussian noise, the proposed RKMCKF algorithm is demonstrated to promote the accuracy of state estimation compared with the conventional Kalman filter, Gaussian sum filter, Huber filter, and maximum correntropy Kalman filter through the simulations.
本文提出了一种基于有理二次核的最大熵卡尔曼滤波器(RKMCKF)算法,以提高非高斯噪声干扰的估计精度。首先,推导出 RKMCKF 算法来消除多维非高斯噪声干扰产生的奇异矩阵。其次,分析了核带宽的上限,提供了核带宽的理论范围,有利于选择合适的核带宽,提高状态估计的精度。此外,还验证了状态估计误差的边界性,以体现 RKMCKF 算法的稳定性。最后,通过仿真证明了在不同类型的非高斯噪声下,与传统卡尔曼滤波器、高斯和滤波器、Huber滤波器和最大熵卡尔曼滤波器相比,所提出的RKMCKF算法提高了状态估计的精度。
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引用次数: 0
Robust blade pitch control of semi-submersible floating offshore wind turbines based on the modified super-twisting sliding-mode algorithm 基于改进的超扭曲滑动模式算法的半潜式浮动海上风力涡轮机叶片螺距稳健控制
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-20 DOI: 10.1016/j.jfranklin.2024.107279
Yong-Chao Liu, Hedi Basbas, Salah Laghrouche
In this paper, a novel robust collective blade pitch controller (CBPC) is proposed for the semi-submersible floating offshore wind turbine (FOWT) above the rated wind speed. The proposed CBPC is based on the modified super-twisting sliding-mode (MSTSM) algorithm. Firstly, based on a control-oriented model of the semi-submersible FOWT, the dynamics of the rotor speed and the platform pitch rate considering the lumped disturbances, which consist of external disturbances, parametric uncertainties and unmodeled dynamics, are derived. Afterward, the MSTSM algorithm-based CBPC (MSTSM-CBPC) is designed for regulating the generator power to its rated value and reducing the platform pitching motion. Comparative co-simulation tests among the gain-scheduling proportional-integral CBPC, the standard STSM algorithm-based CBPC and the proposed MSTSM-CBPC are performed. Simulation results validate the effectiveness and the superiority of the proposed MSTSM-CBPC.
本文针对额定风速以上的半潜式浮动海上风力涡轮机(FOWT)提出了一种新型鲁棒集体叶片变桨控制器(CBPC)。所提出的 CBPC 基于改进的超扭曲滑动模式(MSTSM)算法。首先,基于面向控制的半潜式海上风力涡轮机模型,推导出转子速度和平台变桨率的动态特性,并考虑了由外部干扰、参数不确定性和未建模动态特性组成的叠加干扰。随后,设计了基于 MSTSM 算法的 CBPC(MSTSM-CBPC),用于将发电机功率调节到额定值并减少平台俯仰运动。对增益调度比例积分 CBPC、基于标准 STSM 算法的 CBPC 和所提出的 MSTSM-CBPC 进行了联合仿真比较试验。仿真结果验证了所提出的 MSTSM-CBPC 的有效性和优越性。
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引用次数: 0
Distributed time-varying optimization with prescribed-time approach 采用规定时间方法进行分布式时变优化
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-20 DOI: 10.1016/j.jfranklin.2024.107270
Yong Chen , Jieyuan Yang , Wei Zhong , Tao Yu

This work focuses on distributed time-varying optimization algorithms that can converge in a prescribed time period, both single-integrator systems and double-integrator systems are considered. A nested structure is proposed for applying prescribed-time approach to distributed time-varying optimization problems in this work. For single-integrator systems, the prescribed time interval is divided into three sub-intervals, then the average consensus estimation, the state consensus, and the optimized trajectory tracking are achieved sequentially through the time-scale function in the three sub-time intervals. This nested structure and the properties of the time-scale function ensure that the first-order algorithm is continuous and bounded. Therefore, the algorithm can be extended to double integrator systems by tracking the virtual first-order input signal. The validity of the proposed first-order and second-order algorithms is verified through optimal dynamic trajectory tracking experiments for indoor UAV clusters.

这项工作的重点是能在规定时间内收敛的分布式时变优化算法,既考虑了单积分器系统,也考虑了双积分器系统。本文提出了一种嵌套结构,用于将规定时间方法应用于分布式时变优化问题。对于单积分器系统,规定时间间隔被划分为三个子时间间隔,然后通过三个子时间间隔内的时间尺度函数依次实现平均共识估计、状态共识和优化轨迹跟踪。这种嵌套结构和时间尺度函数的特性确保了一阶算法是连续和有界的。因此,该算法可以通过跟踪虚拟一阶输入信号扩展到双积分器系统。通过对室内无人机集群进行最优动态轨迹跟踪实验,验证了所提出的一阶和二阶算法的有效性。
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引用次数: 0
Adaptive control of bilateral teleoperators with convergent parameter estimation and guaranteed compliance 具有收敛参数估计和保证遵从性的双边远程操纵器自适应控制
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-20 DOI: 10.1016/j.jfranklin.2024.107291
Baorui Jing, Jing Na, Hao Duan, Yantian Li, Xian Wang, Yingbo Huang
Although adaptive control has been studied for teleoperation systems in the past decades, the convergence of parameter estimation is generally difficult to claim in the existing methods, and thus only specific scenarios (e.g., free motion) and partial operation performance (e.g., synchronization) have been addressed. In this paper, we found that the convergence of parameter estimation is crucial for bilateral teleoperation systems to retain the guaranteed operation performances, including compliance in the tracking motion and transparency in the contact motion. Accordingly, this paper suggests an alternative adaptive control for bilateral teleoperation systems, where a new adaptive law with the estimation errors as leakage terms is developed to obtain finite-time convergence of the parameter estimation. This convergent property allows to compensate for the undesired dynamics (e.g., gravity) in the closed-loop system so as to achieve ideal compliance and transparency. The control system’s stability and performances under constant time delays are analyzed for three scenarios: free motion, tracking motion, and contact motion. The quantitative relationship between the joint velocities and the human torques in the tracking motion is also studied, and the transparency is addressed in the contact motion. Simulations and experiments on a Baxter robot all showcase the effectiveness and superiority of the developed approach.
尽管在过去的几十年中已经对远程操纵系统的自适应控制进行了研究,但在现有的方法中,参数估计的收敛性通常很难保证,因此只解决了特定场景(如自由运动)和部分操作性能(如同步)的问题。在本文中,我们发现参数估计的收敛性对于双边远程操纵系统保证运行性能至关重要,包括跟踪运动中的顺从性和接触运动中的透明性。因此,本文为双边远程操纵系统提出了另一种自适应控制方法,即开发一种将估计误差作为泄漏项的新自适应法则,以获得参数估计的有限时间收敛性。这种收敛特性可以补偿闭环系统中的非预期动态(如重力),从而实现理想的顺应性和透明度。分析了控制系统在恒定时间延迟下的稳定性和性能,包括三种情况:自由运动、跟踪运动和接触运动。此外,还研究了跟踪运动中关节速度与人体扭矩之间的定量关系,并探讨了接触运动中的透明度问题。在巴克斯特机器人上进行的模拟和实验都证明了所开发方法的有效性和优越性。
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引用次数: 0
New conditions for stabilization and l2-gain analysis of discrete-time switched systems 离散时间开关系统稳定和 l2 增益分析的新条件
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-20 DOI: 10.1016/j.jfranklin.2024.107207
Yaping Sun , Wei Xing Zheng , Xinsong Yang , Zhengrong Xiang , Housheng Su

This paper uses a time-varying state feedback control method to investigate the global asymptotic stabilization issue of discrete-time switched systems with dwell-time constraints. A discrete dwell-time partitioning technique is proposed to design a time-varying Lyapunov function, which has a distinct characteristic that its value decreases at any time, even at each switching instant. Applying the partitioning technique and the time-varying control method, some new conditions with adjustable computational complexity are derived for stabilizing the discrete-time switched systems. Moreover, the extension to l2-gain computation is presented in the sequel. Four examples are provided to illustrate the merits of the theoretical analysis.

本文采用时变状态反馈控制方法来研究具有驻留时间约束的离散时间切换系统的全局渐近稳定问题。本文提出了一种离散驻留时间分区技术来设计时变 Lyapunov 函数,该函数有一个显著特点,即其值在任何时候都会减小,即使在每个切换瞬间也是如此。应用分区技术和时变控制方法,得出了一些计算复杂度可调的新条件,用于稳定离散时间开关系统。此外,后文还介绍了 l2 增益计算的扩展。本文提供了四个实例来说明理论分析的优点。
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引用次数: 0
Class incremental learning with analytic learning for hyperspectral image classification 高光谱图像分类的类增量学习与分析学习
IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-19 DOI: 10.1016/j.jfranklin.2024.107285
Huiping Zhuang , Yue Yan , Run He, Ziqian Zeng
Hyperspectral image classification (HSIC) is crucial for applications in agriculture and environmental monitoring. As ground objects evolve and remote sensing technology progresses, there is a growing need for HSIC models that can adapt to new data classes without requiring to be retrained from scratch. Throughout the continual learning procedure, the model is expected to not only effectively extract spatial–spectral features from the hyperspectral image but also alleviate the issue of catastrophic forgetting, i.e., the model forgets the learned classes’ knowledge when accessing novel classes during the training process. In this paper, for the HSIC task, we propose a class incremental learning method (HSI-CIL) that is based on analytic learning, a technique that converts network training into linear problems. Specifically, The HSI-CIL model consists of a lightweight feature extractor, a Feature Processing Module (FPM) and an Analytic Linear Classifier (ALC). This model does not need data storage for old and new classes and has only one epoch in the incremental learning stage, so it has lower consumption of resources and training time than several attempts have been proposed for addressing catastrophic forgetting. We perform abundant experiments with the proposed HSI-CIL on three publicly available hyperspectral datasets including Indian Pines, Pavia University, and Salinas. The experiments demonstrate that our HSI-CIL exceeds the state-of-the-art class incremental learning (CIL) techniques applied in HSIC with a certain gap.
高光谱图像分类(HSIC)对于农业和环境监测领域的应用至关重要。随着地面物体的发展和遥感技术的进步,越来越需要能够适应新数据类别而无需从头开始重新训练的 HSIC 模型。在整个持续学习过程中,模型不仅要能有效地从高光谱图像中提取空间光谱特征,还要能缓解灾难性遗忘的问题,即在训练过程中,模型在访问新的类别时会遗忘已学过的类别知识。本文针对 HSIC 任务,提出了一种基于解析学习的类增量学习方法(HSI-CIL),解析学习是一种将网络训练转换为线性问题的技术。具体来说,HSI-CIL 模型由一个轻量级特征提取器、一个特征处理模块(FPM)和一个分析线性分类器(ALC)组成。该模型不需要存储新旧类别的数据,在增量学习阶段只有一个历元,因此与其他几种解决灾难性遗忘的尝试相比,该模型消耗的资源和训练时间更少。我们在三个公开的高光谱数据集(包括印第安松树、帕维亚大学和萨利纳斯)上对所提出的 HSI-CIL 进行了大量实验。实验证明,我们的 HSI-CIL 超越了 HSIC 中应用的最先进的类增量学习(CIL)技术,并存在一定差距。
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引用次数: 0
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Journal of The Franklin Institute-engineering and Applied Mathematics
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