ISA transactions最新文献_第2页

Suppressing torsional drill-string vibrations considering high- and low-frequency disturbances by model reference adaptive control with equivalent-input-disturbance method 等效输入扰动法模型参考自适应控制抑制高低频干扰下钻柱扭振。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2025.12.028

Chengda Lu , Hengyu Huang , Hao Sun , Feixue Jin , Daiki Sato , Jundong Wu

This paper develops a torsional drill-string vibration suppression method based on model reference adaptive control and equivalent-input-disturbance considering high- and low-frequency disturbances. Most existing studies treat the bit–rock interaction merely as an undifferentiated external disturbance and achieve vibration suppression by compensating for it as a whole. However, they often fail to specifically address or decouple the distinct high-frequency and low-frequency components inherently present within the complex disturbance generated. To address this gap, this paper establishes a torsional vibration model of the drill-string. Then, a control scheme for torsional drill-string vibration based on the model reference adaptive control with equivalent-input-disturbance (MRAC-EID) method is developed. The state-dependent low-frequency bit-rock interaction disturbance is suppressed through the MRAC method, and the higher-frequency disturbance caused by the segment flexible characteristics of the drill-string is suppressed through the EID method. The stability analysis of the torsional drill-string vibration suppression system is conducted. Finally, the effectiveness of the developed MRAC-EID method is verified through simulation and micro-rig experiments, showing that the developed method achieves vibration suppression under different formations.

提出了一种基于模型参考自适应控制和等效输入扰动的钻柱扭振抑制方法，同时考虑了高低频扰动。现有的研究大多将钻头-岩石相互作用视为一种未分化的外部扰动，通过整体补偿来实现振动抑制。然而，它们往往不能具体处理或解耦产生的复杂干扰中固有的不同高频和低频成分。为了解决这一问题，本文建立了钻柱扭振模型。在此基础上，提出了一种基于等效输入扰动模型参考自适应控制（MRAC-EID）的钻柱扭振控制方案。通过MRAC方法抑制了状态相关的低频钻头-岩石相互作用干扰，通过EID方法抑制了钻柱分段柔性特性引起的高频干扰。对钻柱扭振抑制系统进行了稳定性分析。最后，通过仿真和微钻机实验验证了所开发的MRAC-EID方法的有效性，表明所开发的方法可以在不同地层条件下实现振动抑制。

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引用次数: 0

4WS and DYC coordinated control for 4WS-4WID autonomous vehicles considering tire nonlinearity 考虑轮胎非线性的4WS- 4wid自动驾驶汽车4WS与DYC协调控制

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2025.12.036

Yuanlong Wang , Jiaqing Zhou , Guanying Chen , Tong Zhang , Changsheng Ma , Rongxian Qiu , Guan Zhou , Chunyan Wang , Wanzhong Zhao

To address the issue of path tracking and stability of four wheel steering and four wheel independent drive (4WS-4WID) autonomous vehicles under extreme conditions, this paper proposes a coordinated control method for four wheel steering (4WS) and direct yaw moment control (DYC). First, a sliding mode observer (SMO) is employed to estimate lateral forces and correct the cornering stiffness, and based on model predictive control (MPC) theory, an adaptive MPC path tracking controller is designed. Then, considering the nonlinear characteristics of tires, the 4WS stability controller and DYC stability controller with nonlinear lateral force are designed by sliding mode control (SMC). On this basis, with the control objectives of sideslip angle and yaw rate, the 4WS weight and DYC weight are coordinated through an extension method to obtain the optimal rear wheel angle and additional yaw moment, ensuring stability control while reducing unnecessary energy waste. Finally, the Carsim-Simulink co-simulation tests and controller-in-the-loop experiment verify the coordinated control strategy can significantly enhance both path tracking accuracy and vehicle stability under extreme conditions.

针对四轮转向和四轮独立驱动（4WS- 4wid）自动驾驶汽车在极端工况下的路径跟踪与稳定性问题，提出了一种四轮转向（4WS）与直接偏航力矩控制（DYC）协调控制方法。首先，采用滑模观测器（SMO）估计侧向力并修正转弯刚度，并基于模型预测控制（MPC）理论设计自适应MPC路径跟踪控制器。然后，考虑轮胎的非线性特性，采用滑模控制（SMC）设计了具有非线性侧力的4WS稳定性控制器和DYC稳定性控制器。在此基础上，以侧滑角和横摆角速度为控制目标，通过延拓法协调4WS重和DYC重，获得最佳后轮角和附加横摆力矩，在保证稳定性控制的同时减少不必要的能量浪费。最后，通过Carsim-Simulink联合仿真试验和控制器在环实验验证了该协调控制策略能显著提高极端工况下的路径跟踪精度和车辆稳定性。

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引用次数: 0

Digital twin-assisted self-supervised contrastive learning: A novel framework for electromechanical equipment fault diagnosis 数字双辅助自监督对比学习：机电设备故障诊断的新框架。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2025.12.010

Jiawei Lu , Chao Lu , Qibing Wang , Yuchen He , Binchun Xia , Xudong Zhang

In modern industry, electromechanical equipment plays a crucial role in ensuring the efficient, stable, and safe operation of production systems. However, fault diagnosis of electromechanical equipment in real industrial environments faces challenges such as a scarcity of labeled data, high cost of fault reproduction, and insufficient generalization across varying operating conditions. In response to these challenges, this paper proposes a novel framework using digital twin-assisted self-supervised contrastive learning for electromechanical equipment fault diagnosis. First, a five-dimensional model for digital twin fault diagnosis of electromechanical equipment (DTEE) is constructed. This model generates simulated data via dynamic simulations of localized faults combined with ten data augmentation methods, alleviating the problem of insufficient fault data and class imbalance. Second, a self-supervised time–frequency contrastive learning model based on digital twin (DT-SSTFCL) is designed to achieve complementary learning of time domain and frequency domain features by using a dual-stream transformer encoder. By learning cross-modal latent relationships through a cross-correlation loss matrix (CCLM), the model better captures intrinsic time–frequency consistency. Furthermore, the smoothed wavelet kernel (SWK) optimization method is proposed, where Laplace wavelet parameters are used as initialization weights of the convolution kernel, and combined with the translation, scaling and smoothing factors to enhance the model’s understanding of the time–frequency features. The experiments are conducted on rolling bearings as an example. The results of three experimental cases show that our method significantly outperforms existing self-supervised and supervised learning methods. This provides a solution for electromechanical equipment fault diagnosis with limited labeled data and across different scenarios.

在现代工业中，机电设备对保证生产系统高效、稳定、安全运行起着至关重要的作用。然而，现实工业环境中机电设备的故障诊断面临着标记数据稀缺、故障再现成本高、不同运行条件下的泛化不足等挑战。针对这些挑战，本文提出了一种新的基于数字孪生辅助自监督对比学习的机电设备故障诊断框架。首先，建立了机电设备数字孪生故障诊断的五维模型。该模型通过对局部故障的动态模拟，结合十种数据扩充方法生成仿真数据，缓解了故障数据不足和类不平衡的问题。其次，设计了基于数字孪生的自监督时频对比学习模型（DT-SSTFCL），利用双流变压器编码器实现时域和频域特征的互补学习。通过相互关联损失矩阵（CCLM）学习跨模态潜在关系，该模型更好地捕获了固有的时频一致性。在此基础上，提出了平滑小波核（SWK）优化方法，将拉普拉斯小波参数作为卷积核的初始化权值，并结合平移、缩放、平滑等因素增强模型对时频特征的理解。以滚动轴承为例进行了试验。三个实验案例的结果表明，我们的方法明显优于现有的自监督和监督学习方法。这为在有限标记数据下、跨场景的机电设备故障诊断提供了一种解决方案。

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引用次数: 0

Coordinated neural adaptive active power control of wind turbines considering pitch system load reduction 考虑桨距系统减载的风力发电机组协调神经自适应有功控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2026.01.005

Xuguo Jiao , Hao Luo , Bo Fan , Xia Chen , Jingbo Zhao , Ruchang Yin

Active power control (APC) is an effective way to address the instability problem caused by high wind energy penetration in power systems. This study presents a coordinated APC scheme to reduce the pitch system’s loads while ensuring accurate active power tracking performance. Firstly, a pitch activation limitation parameter updated by wind speed is designed to expand the rotor speed regulation range. Subsequently, a neural network (NN)-based controller with a segmented weight updating mechanism is designed to achieve smooth and stable pitch angle variations, effectively reducing the pitch system’s loads. Furthermore, we develop a robust differentiator to estimate derivatives of the rotor speed and wind speed thereby avoiding the use of additional sensors. Finally, simulations on the OpenFAST platform demonstrate the effectiveness of our method.

有功功率控制（APC）是解决风电高渗透引起的电力系统不稳定问题的有效途径。本文提出了一种协调的APC方案，以减少俯仰系统的负载，同时保证准确的有功功率跟踪性能。首先，设计了基于风速更新的桨距激活限制参数，扩大了转子的调速范围；在此基础上，设计了基于神经网络的分段权值更新控制器，实现了俯仰角的平稳变化，有效降低了俯仰系统的负载。此外，我们开发了一个鲁棒微分器来估计转子速度和风速的导数，从而避免使用额外的传感器。最后，在OpenFAST平台上进行了仿真，验证了该方法的有效性。

引用次数: 0

Appointed-time fault-tolerant prescribed performance tracking for a rehabilitation exoskeleton with flexible joints using an improved reaching law 使用改进的到达法对具有柔性关节的康复外骨骼进行预约时间容错规定性能跟踪。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2025.12.043

Yong Yang , Hongjun Chen , Deqing Huang , Yanan Li

This article investigates the prescribed performance angular position tracking control of a rehabilitation exoskeleton with uncertain dynamics, unknown disturbances, actuator faults, and flexible joints. First, a novel appointed-time prescribed performance function (APPF) is proposed, wherein the convergence time can be accurately pre-specified. Then, the APPF is integrated with an improved sliding mode reaching law to develop an appointed-time fault-tolerant prescribed performance control (AFPPC) strategy. The attractive features of the proposed AFPPC include: 1) guaranteeing the appointed-time convergence with faster transient response and higher steady-state performance, despite the presence of uncertain dynamics, unknown disturbances, and actuator faults; 2) enhancing the robustness of the system and suppressing the vibration of the flexible joints using an improved reaching-law-based sliding mode prescribed performance framework. These features are capable of improving the safety of the rehabilitation therapy. Lyapunov-based theoretical analysis and comparative simulations demonstrate the benefits of the proposed method.

本文研究了一种具有不确定动力学、未知干扰、驱动器故障和柔性关节的康复外骨骼的规定性能角位置跟踪控制。首先，提出了一种新的指定时间规定性能函数（APPF），该函数可以精确地预先指定收敛时间。然后，将APPF与改进的滑模趋近律相结合，提出了一种指定时间容错规定性能控制（AFPPC）策略。提出的AFPPC的吸引人的特点包括：1)在存在不确定动力学、未知干扰和执行器故障的情况下，以更快的瞬态响应和更高的稳态性能保证指定时间的收敛；2)采用改进的基于到达律的滑模规定性能框架，增强系统的鲁棒性，抑制柔性关节的振动。这些特点能够提高康复治疗的安全性。基于lyapunov的理论分析和仿真对比验证了该方法的有效性。

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引用次数: 0

Adaptive sliding mode fault-tolerant control of an over-actuated hybrid VTOL fixed-wing UAV under transition flight 过渡飞行下过驱动混合垂直起降固定翼无人机的自适应滑模容错控制。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2025.12.046

Ban Wang , Huimin Zhao , Xinyue Hu , Yanyan Shen , Ni Li

In this study, an innovative adaptive sliding mode fault-tolerant control approach is developed for an over-actuated vertical takeoff and landing (VTOL) fixed-wing unmanned aerial vehicle (UAV) with the capability to suppress overestimation of adaptive parameters. This method is designed to effectively address model uncertainties and actuator faults without relying on any previous information regarding the specifics of faults or the boundaries of uncertainties. An innovative adaptive sliding mode control (SMC) mechanism is designed which can autonomously adjust to compensate for the unpredictable nature of these challenges, ensuring the stability and reliability of the UAV system under various operational conditions. Taking into account the over-actuated characteristics of the studied VTOL UAV, a control allocation module is further designed to efficiently distribute the control signals produced by the adaptive SMC scheme. It is noteworthy that the designed adaptive control approach can effectively prevent the overestimation of adaptive parameters, thereby reducing the occurrence of undesired control chattering. Finally, the superiority and efficacy of the designed control technique are convincingly illustrated through an extensive range of comparative hardware-in-the-loop simulation tests.

针对过度驱动垂直起降（VTOL）固定翼无人机（UAV），提出了一种创新的自适应滑模容错控制方法，具有抑制自适应参数高估的能力。该方法旨在有效地解决模型不确定性和执行器故障，而不依赖于任何关于故障细节或不确定性边界的先前信息。设计了一种创新的自适应滑模控制（SMC）机制，可以自主调整以补偿这些挑战的不可预测性，确保无人机系统在各种操作条件下的稳定性和可靠性。针对所研究的垂直起降无人机的过度驱动特性，进一步设计了控制分配模块，对自适应SMC方案产生的控制信号进行有效分配。值得注意的是，所设计的自适应控制方法可以有效地防止自适应参数的高估，从而减少不期望的控制抖振的发生。最后，通过广泛的半实物仿真对比试验，令人信服地说明了所设计控制技术的优越性和有效性。

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引用次数: 0

Dynamic event-triggered prescribed-time observer via parametric Lyapunov equations 通过参数李雅普诺夫方程的动态事件触发的规定时间观测器。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2026.01.006

Jiatong He , Jing Chen , Gang Zheng , Heng Liu , Jinde Cao , Liuxiao Guo , Jiancheng Zhang

This paper is concerned with a prescribed-time observer (PTO) for a class of linear systems by using a novel dynamic event-triggered mechanism (DETM) with bounded triggering conditions. Traditional PTOs often require real-time updates of the measurement output signal, leading to high communication costs. Event-triggered approaches can address this issue. However, event-triggered approaches hardly achieve prescribed-time convergence. In order to achieve fast state estimation while maintaining low communication costs, a dynamic event-triggered prescribed-time observer (DETPTO) is developed by using a parametric Lyapunov equation (PLE), in which the estimation of all system states can also be achieved within a prescribed-time

T

. To achieve this goal, a DETM is proposed by integrating both estimation error and measurement error, ensuring that the observer updates the measurement output only when necessary rather than continuously. Moreover, it is proven that the proposed DETPTO can avoid the Zeno behavior. Finally, numerical simulations validate the effectiveness of the proposed methods.

利用一种具有有界触发条件的动态事件触发机制，研究一类线性系统的规定时间观测器。传统的pto往往需要实时更新测量输出信号，导致通信成本高。事件触发的方法可以解决这个问题。然而，事件触发的方法很难达到规定的时间收敛性。为了在保持低通信成本的同时实现快速状态估计，利用参数Lyapunov方程（PLE）开发了一种动态事件触发的规定时间观测器（DETPTO），该观测器也可以在规定时间t内实现对系统所有状态的估计。为了实现这一目标，提出了一种综合估计误差和测量误差的DETM。确保观测器仅在必要时才更新测量输出，而不是连续更新。此外，还证明了所提出的DETPTO可以避免芝诺行为。最后，通过数值仿真验证了所提方法的有效性。

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引用次数: 0

High-dimensional optimized extraction chirplet transform: Algorithm and applications 高维优化提取啁啾变换：算法与应用。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2026.01.003

Long Ge , Dezun Zhao , Tianyang Wang , Lingli Cui

Under time-varying operating conditions, vibration signals from rotating machinery typically contain dense and non-proportional frequency components, which make it difficult for current time-frequency analysis (TFA) techniques to achieve high-precision and highly concentrated time-frequency representations (TFRs). Accordingly, the high-dimensional optimized extraction chirplet transform (HOECT) is proposed. In the HOECT, a window parameter adaptive optimization criterion is first designed to dynamically match local characteristics of the signal; second, the component matching CT (CMCT) is improved based on the proposed criterion, and its results are mapped into the time-frequency-chirprate domain to separate frequency components; finally, based on estimated local frequency and chirprate, the smoothing extraction operator (SEO) is constructed in the frequency-chirprate domain, which significantly enhances the energy concentration. In addition, a novel connected domain analysis (CDA) algorithm is proposed to effectively suppress strong noise interference and highlight key features of signal components. Simulation results illustrate that the HOECT can accurately characterize dense and non-proportional frequency components with high energy concentration. The superiority of the HOECT in operational state characterization and fault feature identification is further verified through two vibration signals of planetary gearboxes. Additionally, the whale sound signal results indicate that the proposed method exhibits strong robustness and applicability in analyzing complex non-stationary signals.

在时变工况下，旋转机械的振动信号通常包含密集且不成比例的频率成分，这使得当前的时频分析技术难以实现高精度和高度集中的时频表示。据此，提出了高维优化提取小波变换（HOECT）。在HOECT中，首先设计了窗口参数自适应优化准则来动态匹配信号的局部特征；其次，根据提出的准则对分量匹配CT （CMCT）进行改进，并将其结果映射到时-频-chirprate域中分离频率分量；最后，基于估计的局部频率和chirprate，在频率-chirprate域中构造平滑提取算子（SEO），显著提高了能量集中度。此外，提出了一种新的连通域分析（CDA）算法，可以有效地抑制强噪声干扰，突出信号成分的关键特征。仿真结果表明，HOECT能准确表征能量浓度高的密集非比例频率分量。通过行星齿轮箱的两个振动信号，进一步验证了HOECT在运行状态表征和故障特征识别方面的优越性。此外，对鲸声信号的分析结果表明，该方法具有较强的鲁棒性和对复杂非平稳信号分析的适用性。

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引用次数: 0

FGO-Tuned 2-DOF PI controller for pressure regulation in centrifugal fans driven by induction motors using an experimentally validated model 基于实验验证模型的fgo调谐2-DOF PI控制器用于感应电机驱动的离心风机压力调节。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2025.12.012

Cebrail Turkeri , Serdar Ekinci , Davut Izci , Oleh Kiselychnyk

This study proposes a novel pressure control strategy for a centrifugal fan driven by an induction motor, using a two-degree-of-freedom (2-DOF) proportional-integral (PI) controller optimized via the fungal growth optimizer (FGO). Built upon a validated nonlinear model, the FGO algorithm tunes the controller parameters to minimize a cost function reflecting overshoot and tracking error. Comparative evaluations are performed against genetic algorithm (GA), L-SHADE, and the Newton-Raphson-based optimizer (NRBO), as well as classical methods such as Cohen-Coon and Rovira techniques. The FGO-based controller demonstrates superior dynamic response, robustness, and noise immunity. Statistical validation using the Wilcoxon signed-rank test confirms the performance improvements. These results highlight the effectiveness of FGO in real-world pressure regulation and establish a benchmark for modern industrial fan control systems.

本研究提出了一种基于真菌生长优化器（FGO）优化的两自由度（2-DOF）比例积分（PI）控制器的感应电机驱动离心风机压力控制策略。基于经过验证的非线性模型，FGO算法调整控制器参数以最小化反映超调和跟踪误差的代价函数。对遗传算法（GA）、L-SHADE和基于newton - raphson的优化器（NRBO）以及经典方法（如Cohen-Coon和Rovira技术）进行了比较评估。基于fgo的控制器具有良好的动态响应、鲁棒性和抗噪性。使用Wilcoxon sign -rank检验的统计验证证实了性能的改进。这些结果突出了FGO在实际压力调节中的有效性，并为现代工业风扇控制系统建立了基准。

引用次数: 0

A primal-dual approach to double-risk-constrained LQR for practical control under non-Gaussian noise 一种用于非高斯噪声下双风险约束LQR实际控制的原始对偶方法。

IF 6.5 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

ISA transactions

Pub Date : 2026-02-01 DOI: 10.1016/j.isatra.2025.12.039

Xi-Xi Ji , Cheng-Lin Liu , Ya Zhang , Yang-Yang Chen

This paper presents a double-risk-constrained linear quadratic regulator (DRC-LQR) for practical control of partially observable systems under non-Gaussian and biased disturbances. Unlike conventional risk-neutral or single-risk formulations, the proposed approach jointly constrains state and output variability through a computationally tractable primal–dual optimization framework, enabling explicit compensation for noise skewness and heavy tails. As the first infinite-horizon formulation ensuring joint stability and constraint satisfaction under general non-Gaussian conditions, the DRC-LQR achieves both theoretical rigor and real-world feasibility. Comprehensive simulations on aircraft flight control and voltage regulation tasks demonstrate over 60% improvement in regulation accuracy, 93.7% faster convergence, and 99.8% constraint satisfaction compared with standard LQR, confirming its superior robustness and practicality. These results establish DRC-LQR as a systematic and implementable extension of LQR, advancing risk-sensitive control design for safety-critical systems subject to extreme disturbances.

针对非高斯偏扰动下部分可观测系统的实际控制问题，提出了一种双风险约束线性二次型调节器（DRC-LQR）。与传统的风险中性或单风险公式不同，该方法通过可计算的原始对偶优化框架共同约束状态和输出可变性，从而实现对噪声偏度和重尾的显式补偿。作为第一个在一般非高斯条件下保证关节稳定性和约束满足的无限视界公式，DRC-LQR实现了理论严密性和现实可行性。对飞机飞行控制和电压调节任务的综合仿真表明，与标准LQR相比，其调节精度提高了60%以上，收敛速度提高了93.7%，约束满足率提高了99.8%，证明了其优越的鲁棒性和实用性。这些结果确立了DRC-LQR作为LQR的系统和可实施扩展，推进了受极端干扰的安全关键系统的风险敏感控制设计。

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引用次数: 0