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Aircraft human-machine interaction assistant design: A novel multimodal data processing and application framework 飞机人机交互助手设计:新型多模态数据处理和应用框架
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-28 DOI: 10.1049/cth2.12754
Ao Wu, Yang Jin, Maolong Lv, Huanyu Li, Leyan Li, Rennong Yang

During aircraft operations, pilots rely on human-machine interaction platforms to access essential information services. However, the development of a highly usable aerial assistant necessitates the incorporation of two interaction modes: active-command and passive-response modes, along with three input modes: voice inputs, situation inputs, and plan inputs. This research focuses on the design of an aircraft human-machine interaction assistant (AHMIA), which serves as a multimodal data processing and application framework for human-to-machine interaction in a fully voice-controlled manner. For the voice mode, a finetuned FunASR model is employed, leveraging private aeronautical datasets to enable specific aeronautical speech recognition. For the situation mode, a hierarchical situation events extraction model is proposed, facilitating the utilization of high-level situational features. For the plan mode, a multi-formations double-code network plan diagram with a timeline is utilized to effectively represent plan information. Notably, to bridge the gap between human language and machine language, a hierarchical knowledge engine named process-event-condition-order-skill (PECOS) is introduced. PECOS provides three distinct products: the PECOS model, the PECOS state chart, and the PECOS knowledge description. Simulation results within the air confrontation scenario demonstrate that AHMIA enables active-command and passive-response interactions with pilots, thereby enhancing the overall interaction modality.

在飞机运行过程中,飞行员依靠人机交互平台获取必要的信息服务。然而,开发高度可用的空中助手需要结合两种交互模式:主动指挥和被动响应模式,以及三种输入模式:语音输入、情况输入和计划输入。本研究的重点是设计一个飞机人机交互助手(AHMIA),它是一个以全语音控制方式进行人机交互的多模态数据处理和应用框架。对于语音模式,采用微调的FunASR模型,利用私人航空数据集实现特定的航空语音识别。对于情境模式,提出了一种分层的情境事件提取模型,便于高层情境特征的利用。对于规划模式,采用带时间轴的多阵型双码网络规划图有效地表示规划信息。值得注意的是,为了弥合人类语言和机器语言之间的差距,引入了一种名为过程-事件-条件-顺序-技能(PECOS)的分层知识引擎。PECOS提供了三种不同的产品:PECOS模型、PECOS状态图和PECOS知识描述。空中对抗场景中的仿真结果表明,AHMIA能够与飞行员进行主动指挥和被动响应交互,从而增强整体交互方式。
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引用次数: 0
Enhanced stochastic coding framework for discriminating faults and cyber incidents in hybrid systems 用于判别混合系统故障和网络事件的增强型随机编码框架
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-15 DOI: 10.1049/cth2.12744
Mustafa Badr, Heidar Ali Talebi, Mohammad A. Khosravi

This article presents an innovative approach for distinguishing replay attacks from faults in hybrid systems. To develop the idea at first, a novel technique for replay attack detection, which differentiates it from typical system faults, is introduced. This is achieved through a tactical combination of stochastic coding and a window-based comparison mechanism, setting a new standard in hybrid system security. In the realm of fault detection, robust L2-L adaptive observers are employed for precise mode detection, allowing for an accurate assessment of the system's operational state. Additionally, robust H Sliding Mode Observers are utilized to identify abnormal behaviours in the system's output, further solidifying the fault detection capabilities. A significant enhancement in the proposed approach is the integration of a Luenberger observer with the Butterworth low-pass filter. This novel addition not only refines the filtering process but also contributes to the overall reliability and accuracy of the system. The efficiency and versatility of these methods are demonstrated through their application to a four-tank hybrid system. This practical simulation showcases the adaptability of the approach to real-world scenarios, highlighting its potential in diverse applications within the field of hybrid systems.

本文提出了一种区分重放攻击和混合系统故障的创新方法。首先,本文介绍了一种新颖的重放攻击检测技术,它将重放攻击与典型的系统故障区分开来。这是通过随机编码和基于窗口的比较机制的战术组合实现的,为混合系统的安全性设定了新标准。在故障检测领域,采用了鲁棒 L2-L∞ 自适应观测器进行精确的模式检测,从而可以准确评估系统的运行状态。此外,鲁棒 H∞ 滑动模式观测器可用于识别系统输出中的异常行为,进一步巩固故障检测能力。建议方法的一个重大改进是将卢恩伯格观测器与巴特沃斯低通滤波器相结合。这一新颖的添加不仅完善了滤波过程,还有助于提高系统的整体可靠性和准确性。通过将这些方法应用于四油箱混合动力系统,展示了这些方法的效率和多功能性。这一实际模拟展示了该方法在现实世界场景中的适应性,突出了其在混合动力系统领域各种应用中的潜力。
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引用次数: 0
An adaptive EKF-SLAM algorithm for cooperative navigation of multi-aircrafts 多机协同导航的自适应EKF-SLAM算法
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-14 DOI: 10.1049/cth2.12750
Wei Chen, Shan Jiang, Jiarong Cao, Ruisheng Sun

Aiming at cooperative navigation of multi-aircrafts, an adaptive EKF-SLAM algorithm for non-fixed landmark is proposed. First, the aircraft motion model and angle measurement model are established. Second, the fixed landmark cooperative EKF-SLAM algorithm is established. Furthermore, a distributed EKF-SLAM algorithm is designed. Then, the adaptive EKF-SLAM algorithm with non-fixed landmark is proposed. Finally, simulation results verify the effectiveness of the proposed algorithm.

针对多机协同导航问题,提出了一种非固定地标的自适应EKF-SLAM算法。首先,建立了飞行器运动模型和角度测量模型;其次,建立了固定地标协同EKF-SLAM算法;在此基础上,设计了分布式EKF-SLAM算法。然后,提出了不固定地标的自适应EKF-SLAM算法。最后,仿真结果验证了该算法的有效性。
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引用次数: 0
Finite-time lag bipartite synchronization of double-layer networks with non-linear coupling strength and random coupling delays via T-S fuzzy logic theory 通过 T-S 模糊逻辑理论实现具有非线性耦合强度和随机耦合延迟的双层网络的有限时滞双网同步
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-08 DOI: 10.1049/cth2.12746
Degang Yang, Tao Liang, Wanli Zhang

This article discusses finite-time lag bipartite (FETLB) synchronization of double-layer networks with non-linear coupling strength and multiple time delays. The cooperative and competitive interactions between nodes are considered based on signed graphs. To address the non-linear couplings strength, the T-S fuzzy logic theory is used. An intermittent control approach is introduced to achieve FETLB synchronization, effectively minimizing control costs. Moreover, by the Lyapunov functional method, we derive criteria for achieving FETLB synchronization and provide estimations for the synchronization settling time. In addition, numerical simulation affirms the validity of the theoretical findings, showcasing the practical application of the synchronization results in secure communication.

本文讨论了具有非线性耦合强度和多时间延迟的双层网络的有限时滞双网同步(FETLB)问题。基于符号图考虑了节点间的合作和竞争交互。为解决非线性耦合强度问题,采用了 T-S 模糊逻辑理论。为实现 FETLB 同步,引入了一种间歇控制方法,有效地降低了控制成本。此外,通过 Lyapunov 函数方法,我们得出了实现 FETLB 同步的标准,并提供了同步稳定时间的估计值。此外,数值模拟证实了理论结论的正确性,展示了同步结果在安全通信中的实际应用。
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引用次数: 0
A learning-based hierarchical energy management control strategy for hybrid electric vehicles 基于学习的混合动力汽车分层能量管理控制策略
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-08 DOI: 10.1049/cth2.12749
Yanfang Chen, Xuefang Li

In this work, a novel energy management control framework is developed for hybrid electric vehicles (HEVs) driving in car-following scenarios. In order to enhance the energy efficiency while maintaining the driving safety, a hierarchical control approach consisting of an upper level speed tracking control scheme and a lower level energy management control strategy is proposed. For the upper level tracking control system, an iterative learning model predictive control (ILMPC) scheme is developed to guarantee the tracking performance and the driving safety simultaneously. Additionally, a model predictive control (MPC) algorithm is adopted at the lower level to optimize the torque distribution in real-time based on the driving cycles generated by the upper level control system. With the proposed hierarchical control framework, HEVs are able to improve the energy efficiency significantly by taking the advantages of the operational repeatability. The convergence of the proposed control strategy is analyzed rigorously, and its effectiveness is illustrated through numerical simulations.

本文针对混合动力汽车在汽车跟随场景下的行驶,开发了一种新的能量管理控制框架。为了在保证行车安全的同时提高能效,提出了一种由上层速度跟踪控制和下层能量管理控制组成的分层控制方法。针对上层跟踪控制系统,提出了一种迭代学习模型预测控制(ILMPC)方案,同时保证了跟踪性能和行驶安全。下层采用模型预测控制(MPC)算法,根据上层控制系统产生的驱动周期实时优化转矩分配。在提出的分层控制框架下,混合动力汽车能够利用运行可重复性的优势,显著提高能源效率。严格分析了该控制策略的收敛性,并通过数值仿真验证了其有效性。
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引用次数: 0
Novel design method for cascade control structure of electric drives: Closed-form expressions for control gains via pole placement 电力驱动装置级联控制结构的新型设计方法:通过极点布置获得控制增益的闭式表达式
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-07 DOI: 10.1049/cth2.12747
Csaba Budai, Tamás Tóth-Katona, Péter Stumpf

Cascade control structures with inner current and outer speed loop, usually utilizing PI controllers, are widely used for electrical drives to meet high-quality requirements. The present paper introduces design guidelines via pole placement for achieving control gains both in continuous and discrete time preserving the original cascade control structure with the initially applied controllers. This paper also presents an additional prefilter design to eliminate the undesirable effect of the reference integrals. The paper presents closed-form expressions for the control gains as the function of desired damping ratios, the natural angular frequency of the control loop, and machine parameters to achieve the desired system dynamics. The proposed design methodology is demonstrated on brushed DC and permanent magnet synchronous machines.

通常使用 PI 控制器的电流内环和速度外环级联控制结构被广泛用于电气传动,以满足高质量要求。本文介绍了通过极点放置实现连续和离散时间控制增益的设计准则,通过最初应用的控制器保留了原始级联控制结构。本文还介绍了一种额外的预滤波器设计,以消除参考积分的不良影响。本文提出了控制增益的闭式表达式,它是所需阻尼比、控制环自然角频率和机器参数的函数,以实现所需的系统动态。本文在有刷直流电机和永磁同步电机上演示了所提出的设计方法。
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引用次数: 0
Precise orientation control of gimbals with parametric variations using model reference adaptive controller 利用模型参考自适应控制器对有参数变化的万向节进行精确定位控制
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-03 DOI: 10.1049/cth2.12745
Ömer Çakmak, Erdinç Altuğ

This study focuses on a model reference adaptive control method that ensures identical orientation outputs for different prototypes of a two-axis gimbal produced in mass production. In this method, unlike traditional MRAC structures, an MRAC structure is used in conjunction with state feedback control. First, the reasons for the need for an adaptation mechanism in gimbals and why Model Reference Adaptive Control (MRAC) alone won't be sufficient have been discussed. In the first section, various applications of MRAC have also been mentioned. Then, the mathematical foundation of the model reference adaptive controller used in this study is elaborately explained, followed by stability analyses. In the next step, an ideal reference model exhibiting desired behavior and a real system model with different dynamics are created in a simulation environment. This allows a comparison of the adaptation capabilities of only MRAC and MRAC+State Feedback controllers. Based on the information gathered in this section, the recommended approach in the article is tested on a real gimbal system, and the results are shared. The obtained results demonstrate that the MRAC+State Feedback control structure significantly reduces the error in the gimbal's orientation response compared to the reference model.

本研究的重点是一种模型参考自适应控制方法,该方法可确保批量生产的双轴万向节的不同原型具有相同的方向输出。在该方法中,与传统的 MRAC 结构不同,MRAC 结构与状态反馈控制结合使用。首先,我们讨论了万向节需要自适应机制的原因,以及为什么仅有模型参考自适应控制(MRAC)是不够的。第一部分还提到了 MRAC 的各种应用。然后,详细解释了本研究中使用的模型参考自适应控制器的数学基础,随后进行了稳定性分析。下一步,将在仿真环境中创建一个表现出理想行为的理想参考模型和一个具有不同动态特性的真实系统模型。这样就可以比较 MRAC 控制器和 MRAC+ 状态反馈控制器的适应能力。基于本节收集的信息,本文推荐的方法在真实万向节系统上进行了测试,并分享了测试结果。结果表明,与参考模型相比,MRAC+状态反馈控制结构可显著减少万向节方向响应的误差。
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引用次数: 0
Sliding mode control to stabilization of coupled time fractional parabolic PDEs subject to disturbances 滑模控制以稳定受干扰的耦合时间分数抛物 PDEs
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-10-02 DOI: 10.1049/cth2.12743
Jiake Sun, Junmin Wang, Hanwen Zhang

In this article, the stabilization of coupled time fractional parabolic partial differential equations subject to external disturbances is investigated. By using sliding mode control method and backstepping approach, a boundary state feedback controller is designed to reject the matched disturbance and achieve the Mittag-Leffler input-to-state stability of closed-loop system. The existence of the generalized solution to the closed-loop system is proven by Galerkin approximation scheme. Simulations are presented to illustrate the validity of our theoretical results.

本文研究了受外部扰动影响的耦合时分数抛物线偏微分方程的稳定问题。通过使用滑模控制方法和反步法,设计了一个边界状态反馈控制器来拒绝匹配干扰并实现闭环系统的 Mittag-Leffler 输入到状态稳定性。通过 Galerkin 近似方案证明了闭环系统广义解的存在性。仿真结果说明了理论结果的正确性。
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引用次数: 0
Fault-tolerant formation control of multi-agent systems with multiple leaders based on intermediate variable estimator 基于中间变量估计器的多领导多代理系统容错编队控制
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-23 DOI: 10.1049/cth2.12737
Jiantao Shi, Shuangqing Xing, Wenli Zhang, Anning Liu, Chuang Chen

This article investigates the distributed fault-tolerant formation control problem of a multi-leader system with process faults and system uncertainties. This study guarantees all the followers to achieve a specified time-varying formation and track the combination of multiple leaders. By treating faults as a special type of states, an enhanced system is constructed. Furthermore, an intermediate variable observer is designed, but the observer matching condition is not necessary. The observer is used to estimate faults and system uncertainties, for reconstructing the formation controller. The observer gains are determined by solving linear matrix inequalities. Subsequently, controller gains are designed based on Lyapunov theorem and adaptive techniques. Finally, the proposed method is verified through a simulation example.

本文研究了具有过程故障和系统不确定性的多领导系统的分布式容错编队控制问题。该研究保证所有跟随者实现指定的时变编队,并跟踪多个领导者的组合。通过将故障视为一种特殊类型的状态,构建了一个增强型系统。此外,还设计了一个中间变量观测器,但观测器匹配条件并非必要。观测器用于估计故障和系统不确定性,以重建编队控制器。观测器增益通过求解线性矩阵不等式确定。随后,根据 Lyapunov 定理和自适应技术设计控制器增益。最后,通过一个仿真实例验证了所提出的方法。
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引用次数: 0
Cloud-based DMPC structure for velocity consensus and lane following of heterogeneous automated vehicles 基于云的 DMPC 结构,用于异构自动驾驶车辆的速度共识和车道跟随
IF 2.2 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-19 DOI: 10.1049/cth2.12739
Ali Karami Ghanavati, Ali Akbar Safavi, Mohammad Shakerpour

This paper investigates the challenges associated with the velocity consensus and the lane following in heterogeneous automated vehicles considered as agents of a multi agent system. A cloud-based distributed model predictive control structure is proposed to address the distributed intrinsic of such systems. Moreover, for situations that the cloud-based control signal is not reachable, backup controllers based on explicit distributed model predictive control are developed. The proposed cloud-based controller is implemented in the Amazon cloud servers to show the practicality of the proposed approach. Simulation results are presented to demonstrate the effectiveness of our methodology in terms of handling practical limitations of connected and automated vehicles.

本文研究了作为多代理系统代理的异构自动驾驶车辆在速度共识和车道跟随方面所面临的挑战。本文提出了一种基于云的分布式模型预测控制结构,以解决此类系统的分布式固有问题。此外,针对基于云的控制信号无法到达的情况,还开发了基于显式分布式模型预测控制的备用控制器。在亚马逊云服务器中实现了所提出的基于云的控制器,以展示所提方法的实用性。仿真结果展示了我们的方法在处理互联和自动驾驶车辆的实际限制方面的有效性。
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引用次数: 0
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IET Control Theory and Applications
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