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Fully distributed dynamic event-triggered formation-containment control for networked unmanned surface vehicles with intermittent wireless network communications 基于间歇无线网络通信的网络化无人水面车辆全分布式动态事件触发的编队遏制控制。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.10.033
Zhen Zhang, Bing Huang, Xiaotao Zhou, Hua Peng
Favorable neighboring interactions and economical transmission costs are the foundations of formation-containment control (FCC), while the complex marine environments hamper its expansion on networked unmanned surface vehicles (USVs). In this context, this paper investigates an intermittent dynamic event-triggered control scheme for USVs experiencing communication interruptions to achieve FCC. Specifically, the control architecture consists of two synchronously working sub-layers. In the first layer, an intermittent communications-based formation tracking controller is initially developed to endow USVs with higher endurance against communication interruptions, such that the leader USVs can form a desired formation pattern while following a virtual leader. Meanwhile, a dynamic event-triggered mechanism (DETM) is incorporated into the intermittent controller to reduce the update frequency of control signals with computable minimum inter-event time (MIET). Similarly, an intermittent DETM-based controller is proposed for followers to achieve containment missions in the second layer. Moreover, the global information is unnecessary with time-varying control gains. Finally, the simulations are provided to verify the effectiveness and superiority of the proposed control scheme.
良好的相邻相互作用和经济的传输成本是地层遏制控制(FCC)的基础,而复杂的海洋环境阻碍了其在网络化无人水面航行器(usv)上的扩展。在此背景下,本文研究了一种针对通信中断的usv实现FCC的间歇动态事件触发控制方案。具体来说,控制体系结构由两个同步工作的子层组成。在第一层,初步开发了基于间歇通信的编队跟踪控制器,使usv具有更高的抗通信中断能力,使领队usv能够在跟随虚拟领队的同时形成所需的编队模式。同时,在间歇控制器中引入动态事件触发机制(DETM),以可计算最小事件间时间(MIET)降低控制信号的更新频率。同样,在第二层为follower提出了一种基于间歇detm的控制器来实现遏制任务。此外,由于控制增益时变,不需要全局信息。最后通过仿真验证了所提控制方案的有效性和优越性。
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引用次数: 0
A saturation based self-tuned robust control design for Euler Lagrange systems 基于饱和度的欧拉-拉格朗日系统自调整鲁棒控制设计
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.10.020
Hazin Inci , Erman Selim , Enver Tatlicioglu , Erkan Zergeroglu , Aydogan Savran
Control of the family of systems that can be represented in the Euler Lagrange (EL) form is both challenging from a theoretical perspective and applicable to a broad spectrum of real systems. For this type of control problem, given that any parameter estimation error and disturbances are not directly addressed, the system performance deteriorates, and stability cannot be deduced in advance. Considering these issues, this work presents the design and the corresponding analysis of a saturation function based, model-free, continuous robust controller for mechanical systems represented in the EL form. In order to avoid chattering in controller input, which is a common problem in most robust and high-gain control designs, the proposed method makes use of continuously differentiable terms. The stability of the closed-loop system is ensured via rigorous Lyapunov-based arguments. To ease the tuning of the controller gain, an adaptive gain-tuning algorithm is proposed to be applied as an add-on. The effectiveness of the controller is demonstrated by a simulation study on a twin rotor multi-input–multi-output system (TRMS) model Furthermore, the feasibility of the proposed method is then tested on an in-house built, inherently unstable, and therefore extremely sensitive mobile robotic platform. In the experimental study, satisfactory performances are attained for both the controller and the gain-tuning algorithm where less than 0.5° error is obtained in roll and pitch angles and less than 1° error is achieved in the yaw direction.
对可以用欧拉-拉格朗日(EL)形式表示的系统系列进行控制,从理论角度看具有挑战性,但也适用于广泛的实际系统。对于这类控制问题,由于任何参数估计误差和干扰都无法直接解决,系统性能会恶化,稳定性也无法预先推断。考虑到这些问题,本研究提出了一种基于饱和函数、无模型、连续鲁棒控制器的设计和相应分析,适用于以 EL 形式表示的机械系统。为了避免大多数鲁棒和高增益控制设计中常见的控制器输入颤振问题,所提出的方法使用了连续可微分项。通过基于 Lyapunov 的严格论证,确保了闭环系统的稳定性。为了简化控制器增益的调整,提出了一种自适应增益调整算法作为附加算法。通过对双转子多输入多输出系统(TRMS)模型的仿真研究,证明了该控制器的有效性。此外,还在内部构建的、本质上不稳定、因此极其敏感的移动机器人平台上测试了所提方法的可行性。在实验研究中,控制器和增益调整算法都获得了令人满意的性能,滚动角和俯仰角误差小于 0.5°,偏航方向误差小于 1°。
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引用次数: 0
Approximate tracking control for nonlinear multi-player systems with deferred asymmetric time-varying full-state constraints 具有延迟非对称时变全状态约束的非线性多玩家系统的近似跟踪控制。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.10.017
Jinguang Wang , Chunbin Qin , Jingyu Wang , Tingting Yang , Hongru Zhao
This paper proposes a set of Nash equilibrium tracking control strategies based on mixed zero-sum (MZS) game for the continuous-time nonlinear multi-player systems with deferred asymmetric time-varying (DATV) full-state constraints and unknown initial state. Firstly, an improved shift transformation is used to modify the original constrained system with an unknown initial state into a barrier transformable constrained system. Then, based on the barrier transformable constrained system and predefined reference trajectory, an unconstrained augmented system is formed through the application of the barrier function (BF) transformation. Furthermore, the MZS game Nash equilibrium tracking control strategies are derived by establishing the tracking error related quadratic cost functions and corresponding HJ functions for different players. On this basis, a critic-only structure is established to approximate the control strategy of every player online. By employing Lyapunov theory, it is proven that the neural network weights and tracking error are uniformly ultimately bounded (UUB) within DATV full-state constraints. Simulation experiments of a three-player nonlinear system demonstrate that our algorithm successfully handles deferred state constraints and unknown initial conditions, ensuring that the system states follow the desired reference trajectories. Simulation results further validate the uniform ultimate boundedness of neural network weights and tracking errors.
本文针对具有延迟非对称时变(DATV)全状态约束和未知初始状态的连续时间非线性多玩家系统,提出了一套基于混合零和博弈(MZS)的纳什均衡跟踪控制策略。首先,利用改进的移位变换将初始状态未知的原始约束系统修改为障碍可变换约束系统。然后,在可障碍变换约束系统和预定参考轨迹的基础上,通过应用障碍函数(BF)变换形成无约束增强系统。此外,通过建立与跟踪误差相关的二次成本函数和相应的 HJ 函数,推导出不同博弈者的 MZS 博弈纳什均衡跟踪控制策略。在此基础上,建立了一种纯批判结构,以近似在线计算每个博弈方的控制策略。通过运用 Lyapunov 理论,证明了在 DATV 满状态约束下,神经网络权重和跟踪误差是均匀最终有界的(UUB)。三人非线性系统的仿真实验表明,我们的算法成功地处理了延迟状态约束和未知初始条件,确保系统状态遵循所需的参考轨迹。仿真结果进一步验证了神经网络权重和跟踪误差的统一终极约束性。
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引用次数: 0
A bearing fault diagnosis method for unknown operating conditions based on differentiated feature extraction 基于差异化特征提取的未知运行条件下轴承故障诊断方法。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.10.024
Wei Cao, Zong Meng, Jimeng Li, Yang Guan, Jingjing Fan, Huihui He, Fengjie Fan
Under unknown operating conditions, the domain generalization approach based on domain metrics is commonly used for rolling bearing fault diagnostics. Nevertheless, in the event of equipment failure under unknown operating conditions, focusing solely on the transferable characteristics across domains may result in the unintentional neglect of domain-specific features. To address the problems mentioned, the present study introduces a feature decomposition learning method that simultaneously extracts inter-domain transferable and domain-specific features. This method aims to obtain richer feature information by constructing different feature extractors. For the extraction of transferable features, a joint metric method based on central moment differences is devised. A difference maximization method is employed to extract domain-specific features. The experimental findings demonstrate that the proposed technique exhibits greater defect detection capacity across two datasets.
在未知运行条件下,基于域指标的域泛化方法通常用于滚动轴承故障诊断。然而,在未知运行条件下发生设备故障时,只关注跨领域的可迁移特征可能会无意中忽略特定领域的特征。为解决上述问题,本研究引入了一种特征分解学习方法,可同时提取跨领域可转移特征和特定领域特征。该方法旨在通过构建不同的特征提取器来获取更丰富的特征信息。为了提取可转移特征,我们设计了一种基于中心矩差的联合度量方法。采用差值最大化方法提取特定领域的特征。实验结果表明,所提出的技术在两个数据集上表现出更强的缺陷检测能力。
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引用次数: 0
Robust estimation method for power system dynamic synchronization with sensor gain degradation 传感器增益衰减情况下电力系统动态同步的鲁棒估计方法。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.10.031
Yi Wang , Jiawei Zhang , Yaoqiang Wang , Zhongwen Li , Kewen Wang , Jun Liang
Efficient and accurate real-time estimation of power system synchronization is quite important for its safety control and operation. However, signal sensing failure, electromagnetic interference, system delay, etc., will cause the sensor gain degradation. To furnish a dependable method for dynamic estimation in power grid synchronization amid sensor gain degradation, this research presents a robust estimation system capable of monitoring and tracking the frequency, voltage phase angles, and magnitudes. Firstly, the random degradation of measurement data is characterized by a discrete distribution within the range [0,1]. Secondly, the state space model of sensor gain degradation is established. Subsequently, a novel modified fault-tolerant extended Kalman filter (MFTEKF) is developed under the recursive estimator framework. Finally, extensive experimental results definitively demonstrate that the proposed MFTEKF can accurately monitor the dynamic characteristics of the power grid.
高效、准确的电力系统同步实时估算对于电力系统的安全控制和运行相当重要。然而,信号传感故障、电磁干扰、系统延迟等都会导致传感器增益衰减。为了在传感器增益衰减的情况下提供可靠的电网同步动态估算方法,本研究提出了一种能够监测和跟踪频率、电压相位角和幅值的鲁棒估算系统。首先,测量数据的随机衰减以 [0,1] 范围内的离散分布为特征。其次,建立传感器增益衰减的状态空间模型。随后,在递归估计器框架下开发了一种新颖的改进型容错扩展卡尔曼滤波器(MFTEKF)。最后,大量实验结果明确表明,所提出的 MFTEKF 能够准确监测电网的动态特性。
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引用次数: 0
Off-policy reinforcement-learning-based fault-tolerant H∞ control for topside separation systems with time-varying uncertainties 基于非策略强化学习的容错 H∞ 控制,用于具有时变不确定性的顶部分离系统。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.11.002
Yuguang Zhang , Juan Wang , Shaobao Li , Xiaoyuan Luo , Xinping Guan
The topside separation system plays a pivotal role in the treatment of produced water within offshore oil and gas production operations. Due to high-humidity and salt-infested marine environments, topside separation systems are susceptible to dynamic model variations and valve faults. In this work, fault-tolerant control (FTC) of topside separation systems subject to structural uncertainties and slugging disturbances is studied. The system is configured as a cascade structure, comprising a water level control subsystem and a pressure-drop-ratio (PDR) control subsystem. A fault-tolerant H control framework is developed to cope with actuator faults and slugging disturbances. To enhance control performance in the presence of actuator faults and model uncertainties while reducing sensitivity to slugging disturbances, the fault-tolerant H control problem for the topside separation system is established as the two-player differential game problem. In addition, a Nash equilibrium solution for the fault-tolerant H control problem is achieved through the solution of the game algebraic Riccati equation (GARE). A model-free approach is presented to implement the proposed fault-tolerant H control method using off-policy reinforcement learning (RL). Simulation studies demonstrate the effectiveness of the solution.
在近海油气生产作业中,顶部分离系统在处理采出水方面发挥着关键作用。由于海洋环境湿度大、盐分多,顶部分离系统很容易受到动态模型变化和阀门故障的影响。在这项工作中,研究了受结构不确定性和抽吸干扰影响的顶部分离系统的容错控制(FTC)。该系统采用级联结构,由水位控制子系统和压降比 (PDR) 控制子系统组成。开发了一个容错 H∞ 控制框架,以应对执行器故障和淤积干扰。为了提高执行器故障和模型不确定性情况下的控制性能,同时降低对拖曳干扰的敏感性,将上部分离系统的容错 H∞ 控制问题建立为双人微分博弈问题。此外,还通过求解博弈代数里卡提方程(GARE)实现了容错 H∞ 控制问题的纳什均衡解。本文提出了一种无模型方法,利用非策略强化学习(RL)来实现所提出的容错 H∞ 控制方法。仿真研究证明了该解决方案的有效性。
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引用次数: 0
State estimation of networked nonlinear systems with aperiodic sampled delayed measurement 网络非线性系统的状态估计与非周期性采样延迟测量。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.11.029
Xincheng Zhuang, Yang Tian, Haoping Wang
This paper aims to study the remote state estimation of networked nonlinear systems subject to aperiodic sampled delayed measurement. A novel sampled-data non-affine nonlinear observer (SNNO) is designed to address this issue. The designed observer is composed of two parts: the first part is a continuous-time observer, and the second part is an auxiliary variable design that provides continuous compensation of output estimation errors for the first part’s state observer. The design of this auxiliary variable provides a new compensation scheme for sampled delayed measurement. The input-to-state stability of the SNNO with respect to the system and output disturbance is proved by means of trajectory-based stability theory. The new theoretical tool reveals the relationship between the convergence rate of the proposed SNNO and the sampling and delay periods. Simulations and comparative analyses with other sampled-data observers are given.
本文旨在研究网络非线性系统在非周期性采样延迟测量条件下的远程状态估计。为解决这一问题,本文设计了一种新颖的采样数据非非线性观测器(SNO)。所设计的观测器由两部分组成:第一部分是连续时间观测器,第二部分是辅助变量设计,用于连续补偿第一部分状态观测器的输出估计误差。该辅助变量的设计为采样延迟测量提供了一种新的补偿方案。通过基于轨迹的稳定性理论,证明了 SNNO 相对于系统和输出扰动的输入到状态稳定性。新的理论工具揭示了拟议 SNNO 的收敛速率与采样和延迟周期之间的关系。文中还给出了模拟结果以及与其他采样数据观测器的比较分析。
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引用次数: 0
Fault detection and classification of motor bearings under multiple operating conditions 多种运行条件下电机轴承的故障检测和分类。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.11.008
Muhammad Asim Abbasi , Shiping Huang , Aadil Sarwar Khan
The article presents a framework for fault detection and classification to monitor the condition of motor bearings under multiple operating conditions. The condition monitoring of motor bearings is crucial for failure prevention, as bearings are prone to failure in challenging working environments. Intelligent fault diagnosis methods driven by deep learning and model-based approaches have been widely adopted to address these concerns. However, accurately diagnosing bearing faults across varying conditions and identifying multiple fault types remains challenging. The article proposes a multitask fault detection and classification approach for health monitoring using the HUST motor bearings dataset. The evaluation using HUST motor bearing datasets demonstrates robust performance across diverse operating conditions and in the presence of multiple faults. The HUST dataset is valuable for bearing fault diagnosis due to its diverse operating conditions and inclusion of multiple fault types, offering a realistic representation of fault scenarios derived from real bearing experiments. This methodology enhances the safety and reliability of mechanical equipment, with adaptability to various rotating scenarios.
文章介绍了一种故障检测和分类框架,用于监控电机轴承在多种运行条件下的状态。电机轴承的状态监测对于故障预防至关重要,因为轴承在具有挑战性的工作环境中很容易发生故障。由深度学习和基于模型的方法驱动的智能故障诊断方法已被广泛采用,以解决这些问题。然而,在不同条件下准确诊断轴承故障并识别多种故障类型仍具有挑战性。文章利用哈工大电机轴承数据集提出了一种用于健康监测的多任务故障检测和分类方法。使用 HUST 电机轴承数据集进行的评估表明,该方法在不同的运行条件下和存在多种故障时都能表现出稳健的性能。HUST 数据集具有多种运行条件,包含多种故障类型,真实再现了从实际轴承实验中得出的故障情况,因此对轴承故障诊断非常有价值。这种方法可提高机械设备的安全性和可靠性,并能适应各种旋转情况。
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引用次数: 0
Dynamic event-triggered tracking control for high-order nonlinear systems with time-varying irregular full-state constraints and input saturation 具有时变不规则全状态约束和输入饱和的高阶非线性系统的动态事件触发跟踪控制。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.11.015
Yan Jiang, Zhong Guo
This paper investigates the unified tracking control problem for a class of high-order nonlinear systems with 7 kinds of irregular state constraints and input saturation based on the dynamic event-triggered mechanism. The irregular state constraints exist in practical systems, including time-varying constraints, alternation between positive and negative bounds, adding/removing constraints during system operation, and the state of the system being constrained only by the upper/lower boundaries. Auxiliary constraint boundaries are introduced to deal with these irregular state constraints. This unified method allows different auxiliary constrained boundaries in response to specific circumstances, without affecting the controller’s structure. Nonlinear transformed functions (NTFs) are used to eliminate the feasibility condition of barrier Lyapunov functions (BLFs) methods. Subsequently, based on the dynamic event-triggered mechanism and adding a power integrator technique, an event-triggered controller is designed to effectively reduce communication burden and energy consumption between the controller and the actuator. Finally, a simulation example and a practical example are given to verify the effectiveness of the proposed unified control method.
基于动态事件触发机制,研究了一类具有7种不规则状态约束和输入饱和的高阶非线性系统的统一跟踪控制问题。实际系统中存在不规则状态约束,包括时变约束、正、负边界交替、系统运行过程中添加/移除约束、系统状态仅受上下边界约束等。引入辅助约束边界来处理这些不规则状态约束。这种统一的方法允许根据具体情况设置不同的辅助约束边界,而不会影响控制器的结构。采用非线性变换函数(NTFs)消除了势垒李雅普诺夫函数(BLFs)方法的可行性条件。随后,基于动态事件触发机制,加入功率积分器技术,设计了事件触发控制器,有效降低了控制器与执行器之间的通信负担和能耗。最后,通过仿真和实际算例验证了所提统一控制方法的有效性。
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引用次数: 0
A layer-wise melting defects mitigation method in laser powder bed fusion process based on machine learning and fuzzy inference 基于机器学习和模糊推理的激光粉末床熔化过程中的分层熔化缺陷缓解方法。
IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2025-01-01 DOI: 10.1016/j.isatra.2024.11.010
Chenguang Ma, Yingjie Zhang
Melting defects in Laser Powder Bed Fusion (LPBF) processes, such as lack of fusion (LOF) or over-melting (OM), can cause significant deterioration in mechanical properties and surface roughness of printed parts, potentially leading to process failure. Previous attempts to utilize local melt pool-related information for LPBF process control have faced limitations due to the high requirements on sensors and data processing, as well as the lack of representativeness of local melt pool information. This study focuses on the surface quality of the parts and proposes an image based LPBF control to mitigate melting defect. A quality identification module utilizing convolutional neural networks (CNN) to perform layer-by-layer evaluation of the melting quality of the part. The CNN achieved an accuracy of up to 98.2% in identifying melting quality. Furthermore, based on the surface melting quality extracted by CNN, a fuzzy control strategy (FIC) integrated with a historical state consistency check mechanism (HSCCM) is introduced to determine the optimal control actions for subsequent layers. Experimental results affirm that the FIC integrated with HSCCM effectively alleviates surface melting defects, thereby enhancing surface roughness and manufacturing quality of components. This research offers a novel approach for online quality monitoring and improvement in LPBF processes.
激光粉末床熔融(LPBF)工艺中的熔融缺陷,如熔融不足(LOF)或熔融过度(OM),会导致印刷部件的机械性能和表面粗糙度显著下降,甚至可能导致工艺失败。由于对传感器和数据处理的要求较高,以及局部熔池信息缺乏代表性,以往利用局部熔池相关信息进行 LPBF 工艺控制的尝试面临诸多限制。本研究重点关注零件的表面质量,并提出了一种基于图像的 LPBF 控制方法,以减少熔化缺陷。质量识别模块利用卷积神经网络(CNN)对零件的熔化质量进行逐层评估。卷积神经网络识别熔化质量的准确率高达 98.2%。此外,根据 CNN 提取的表面熔化质量,引入了与历史状态一致性检查机制(HSCCM)相结合的模糊控制策略(FIC),以确定后续层的最佳控制行动。实验结果表明,与 HSCCM 相结合的模糊控制策略能有效缓解表面熔化缺陷,从而提高部件的表面粗糙度和制造质量。这项研究为 LPBF 工艺的在线质量监控和改进提供了一种新方法。
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引用次数: 0
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