European Journal of Control最新文献

英文中文

Identification of multiple frequency response points using gain-changing nonlinear feedback experiments 利用变增益非线性反馈实验辨识多频响点

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-12-13 DOI: 10.1016/j.ejcon.2025.101437

Julio-Ariel Romero-Pérez , Oscar Miguel-Escrig , José Sánchez-Moreno , Sebastián Dormido-Bencomo

Relay feedback experiments are well known for providing valuable information about system dynamics, which can be used for automatic PID controller tuning. The estimation of frequency response points from data obtained in such experiments is typically based on describing function theory, which assumes purely sinusoidal closed-loop responses and neglects higher-order harmonics. However, this assumption is often violated in low-order systems with poor filtering characteristics, resulting in reduced estimation accuracy. To address this issue, several alternatives, such as the saturation relay and pre-load relay, have been proposed in the literature, offering improved estimation performance. In this work, it is introduced a gain-changing nonlinear scheme for frequency points identification that enhances the accuracy of existing approaches. The experiments follow a similar structure to standard relay feedback tests, thus preserving their well-known advantages while significantly reducing estimation errors. Furthermore, by incorporating calculated time delays and dynamically adjusting the gain-changing parameters, the method generates multiple closed-loop oscillation conditions to identify several frequency response points, all while keeping the output amplitude within safe operational limits. Simulation results demonstrate a substantial improvement in estimation accuracy compared to both traditional and enhanced relay-based methods, offering a precise and practical solution for frequency response identification in industrial process control.

继电器反馈实验以提供有关系统动力学的有价值的信息而闻名，这些信息可用于自动PID控制器调谐。从这些实验中获得的数据中估计频率响应点通常基于描述函数理论，该理论假设纯正弦闭环响应并忽略高阶谐波。然而，这个假设在滤波特性差的低阶系统中经常被违背，导致估计精度降低。为了解决这个问题，文献中提出了几种替代方案，如饱和继电器和预负载继电器，提供了改进的估计性能。在这项工作中，引入了一种增益变化的非线性频率点识别方案，提高了现有方法的精度。实验遵循与标准继电器反馈测试相似的结构，从而保留了其众所周知的优点，同时显着降低了估计误差。此外，通过结合计算的时间延迟和动态调整增益变化参数，该方法产生多个闭环振荡条件以识别多个频率响应点，同时保持输出幅度在安全运行范围内。仿真结果表明，与传统的和增强的基于继电器的方法相比，估计精度有了很大的提高，为工业过程控制中的频率响应识别提供了精确和实用的解决方案。

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引用次数: 0

Kullback-Leibler divergence-based filter design against bias injection attacks 针对偏置注入攻击的基于Kullback-Leibler散度的滤波器设计

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-12-04 DOI: 10.1016/j.ejcon.2025.101427

Fatih Emre Tosun , André M.H. Teixeira , Jingwei Dong , Anders Ahlén , Subhrakanti Dey

Cyber-physical systems (CPS) are increasingly deployed in safety-critical applications, making them prime targets for adversarial attacks. Timely detection and mitigation of such attacks are imperative for the safe operation of CPS. This paper proposes a novel residual generator design method for enhanced detection of bias injection attacks (BIAs) in linear CPS driven by white Gaussian noise. Specifically, we define a flexible attack impact metric based on the weighted norm of the injected bias and a detectability metric based on the Kullback-Leibler divergence. Using these two metrics, we characterize the worst-case BIAs as those that minimize detectability while maintaining a specified minimum impact. For residual generation filter synthesis, we formulate two optimization problems: one for maximizing the detectability of worst-case BIAs at the attack onset and the other at steady state. Since these two problems are inherently conflicting, we employ the ϵ-constraint method to obtain Pareto-optimal solutions that balance transient and steady-state detectability. The effectiveness of the proposed filter design method is demonstrated through numerical simulations, with a comparison against two state-of-the-art benchmarks: the Kalman filter and the

H_{-} / H_{2}

filter.

网络物理系统（CPS）越来越多地部署在安全关键应用中，使其成为对抗性攻击的主要目标。及时发现和缓解此类攻击对于CPS的安全运行至关重要。提出了一种新的残差发生器设计方法，用于增强检测高斯白噪声驱动下的线性CPS中的偏置注入攻击。具体来说，我们定义了一个基于注入偏差加权范数的灵活攻击影响度量和一个基于Kullback-Leibler散度的可检测度量。使用这两个指标，我们将最坏情况BIAs描述为在保持指定最小影响的同时最小化可检测性的偏差。对于残差产生滤波器的合成，我们提出了两个优化问题：一个是在攻击开始时最大限度地检测最坏偏差，另一个是在稳态时最大限度地检测最坏偏差。由于这两个问题本质上是冲突的，我们采用ϵ-constraint方法来获得平衡暂态和稳态可探测性的帕累托最优解。通过数值模拟证明了所提出的滤波器设计方法的有效性，并与两种最先进的基准：卡尔曼滤波器和H - /H2滤波器进行了比较。

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引用次数: 0

Settling time analysis of a continuum model with finite-time target tracking 有限时间目标跟踪连续体模型的沉降时间分析

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-12-03 DOI: 10.1016/j.ejcon.2025.101424

Woojoo Shim , Hyunjin Ahn

We provide a sufficient framework concerning finite-time tracking to a predetermined target of continuum agents. For this, we propose a continuum model derived via the continuum limit of a multi-agent system studied in existing literature. By employing a suitable Lyapunov functional, along with several finite-time stability frameworks, the non-smooth LaSalle invariance principle, and settling time analysis, we establish the desired finite-time tracking under admissible data consisting of initial data, kernel functionals, and system parameters. Finally, we complement and validate our theoretical analysis with numerical simulations that illustrate the results and highlight their practical implications.

我们提供了一个足够的框架关于有限时间跟踪到一个预定目标的连续介质。为此，我们提出了一个连续体模型，该模型是通过现有文献中研究的多智能体系统的连续体极限推导出来的。通过采用合适的Lyapunov泛函，结合几种有限时间稳定性框架、非光滑LaSalle不变性原理和稳定时间分析，在由初始数据、核函数和系统参数组成的可接受数据下，建立了期望的有限时间跟踪。最后，我们用数值模拟来补充和验证我们的理论分析，以说明结果并强调其实际意义。

引用次数: 0

Continuous trajectory planning for non-convex utility functions using hybrid optimization 基于混合优化的非凸效用函数连续轨迹规划

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-12-02 DOI: 10.1016/j.ejcon.2025.101425

He Hao , Daniel Silvestre , Carlos Silvestre

Efficient trajectory generation is essential for applications such as environmental monitoring using autonomous systems, where navigating complex, non-convex environments poses significant challenges. In this paper, we introduce a novel hybrid continuous optimization method that extends gradient techniques to continuous-time frameworks for trajectory planning in non-convex landscapes. The method combines adaptive step-size adjustments with momentum-based gradient techniques, enabling robust navigation through plateau regions and accurate convergence to optimized trajectories. We apply the method to drone trajectory optimization in environments modeled by Gaussian Mixture Models (GMMs), specifically focusing on wildfire monitoring in northern Mexico. The proposed approach generates smooth trajectories and achieves faster convergence when compared to traditional discrete and continuous methods without the hybrid adaptation. Simulation results showcase the method’s potential for broader applications in control systems and other domains requiring optimization in high-dimensional non-convex environments.

高效的轨迹生成对于使用自主系统的环境监测等应用至关重要，在这些应用中，导航复杂的非凸环境构成了重大挑战。在本文中，我们介绍了一种新的混合连续优化方法，将梯度技术扩展到连续时间框架中，用于非凸景观的轨迹规划。该方法将自适应步长调整与基于动量的梯度技术相结合，实现了高原区域的鲁棒导航和优化轨迹的精确收敛。我们将该方法应用于高斯混合模型（GMMs）模拟环境中的无人机轨迹优化，特别关注墨西哥北部的野火监测。与传统的离散和连续方法相比，该方法可以产生平滑的轨迹，并且在没有混合自适应的情况下收敛速度更快。仿真结果表明，该方法在控制系统和其他需要在高维非凸环境中优化的领域具有更广泛的应用潜力。

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引用次数: 0

Approximations of the set of trajectories, attainable sets and integral funnel of the control system with mixed constraints on the control functions 控制函数上有混合约束的控制系统的轨迹集、可达集和积分漏斗的逼近

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-12-01 DOI: 10.1016/j.ejcon.2025.101422

Nesir Huseyin , Anar Huseyin , Khalik G. Guseinov , Vladimir N. Ushakov

In this paper, the set of trajectories, attainable sets and integral funnel of a control system described by an ordinary differential equation are studied. The system is nonlinear with respect to the phase state vector and affine with respect to the control vector. It is assumed that the admissible control functions satisfy mixed constraints, including both integral and geometric constraints. Step by step, the set of admissible control functions is replaced by a set consisting of a finite number of piecewise-constant control functions that generate a finite number of trajectories. First, an error evaluation between the set of trajectories and the set consisting of a finite number of trajectories is presented. Then, the trajectories generated by the piecewise-constant control functions are changed with Euler’s broken lines, and an error estimation between the set of trajectories of the system and the set consisting of a finite number of Euler’s broken lines is obtained. Similar estimations for attainable sets of the system are also provided. By applying these results, we derive an approximation with error evaluation for the integral funnel of the system. It is shown that by appropriately defining discretization parameters, the Hausdorff distance between the set of trajectories, the attainable sets, the integral funnel and their approximations can be made sufficiently small. The impact of upper bounds of the geometric and integral constraints on the presented approximations is discussed.

本文研究了用常微分方程描述的控制系统的轨迹集、可得集和积分漏斗。系统相对于相态矢量是非线性的，相对于控制矢量是仿射的。假设允许控制函数满足混合约束，包括积分约束和几何约束。一步一步地，可容许的控制函数集被一个由有限数量的分段常数控制函数组成的集所取代，这些控制函数产生有限数量的轨迹。首先，给出了轨迹集与由有限个轨迹组成的轨迹集之间的误差评估。然后，将分段常数控制函数生成的轨迹用欧拉折线变换，得到了系统轨迹集与有限条欧拉折线集之间的误差估计。对系统的可达到的集合也提供了类似的估计。利用这些结果，我们得到了系统积分漏斗的一个带误差评价的近似。结果表明，通过适当地定义离散化参数，可以使轨迹集、可达集、积分漏斗及其近似之间的豪斯多夫距离足够小。讨论了几何约束和积分约束的上界对所提出的近似的影响。

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引用次数: 0

Asymptotic boundedness and exponential stability of neutral stochastic functional differential equations with unbounded delay 具有无界时滞中立型随机泛函微分方程的渐近有界性和指数稳定性

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-12-01 DOI: 10.1016/j.ejcon.2025.101423

Wei Mao , Xiaomu Ling , Jie He , Fuke Wu , Xuerong Mao

This paper is concerned with the asymptotic boundedness and exponential stability of neutral stochastic functional differential equations with unbounded delay. Under the Khasminskii-type condition, we establish the LaSalle theorem for the underlying equations to locate its limit set, and obtain some criteria on the asymptotic boundedness and almost sure stability. By means of the Lyapunov function, some conditions are given for the moment asymptotic boundedness and exponential stability of neutral stochastic functional differential equations with unbounded delay. These conditions also indicate the almost sure exponential stability is robust with respect to stochastic perturbation. Finally, two examples are presented to illustrate our results.

研究了具有无界时滞的中立型随机泛函微分方程的渐近有界性和指数稳定性。在khasminskii型条件下，我们建立了底层方程的LaSalle定理，并得到了其极限集的渐近有界性和几乎确定稳定性的判据。利用Lyapunov函数，给出了具有无界时滞的中立型随机泛函微分方程的矩渐近有界性和指数稳定性的一些条件。这些条件还表明，对于随机扰动，几乎肯定的指数稳定性是鲁棒的。最后，给出了两个例子来说明我们的结果。

引用次数: 0

DREM-based predefined-time adaptive learning control for nonlinear systems with actuator faults and input delay 具有执行器故障和输入延迟的非线性系统基于drem的预定义时间自适应学习控制

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-11-27 DOI: 10.1016/j.ejcon.2025.101426

Mohamed Kharrat

This paper addresses the problem of adaptive tracking control for a class of strict-feedback nonlinear systems subject to actuator faults, input delays, and model uncertainties via parameter identification algorithm. To mitigate the adverse effects of input delay, a Pade approximation combined with an intermediate variable is employed. A parameter estimation method utilizing a three-layer transformation is designed to achieve predefined-time convergence while eliminating the need for persistent excitation. To avoid singularities inherent in traditional control laws, a smooth hyperbolic tangent function is integrated into the design. Furthermore, a composite learning framework is introduced within the adaptive dynamic surface control structure, enabling predefined-time error convergence. Lyapunov-based analysis confirms semi-global uniformly predefined-time boundedness of the closed-loop system. Simulation results validate the effectiveness and robustness of the proposed control strategy.

针对一类存在执行器故障、输入延迟和模型不确定性的严格反馈非线性系统，采用参数辨识算法研究了自适应跟踪控制问题。为了减轻输入延迟的不利影响，采用了结合中间变量的Pade近似。设计了一种利用三层变换的参数估计方法来实现预定义时间收敛，同时消除了对持续激励的需要。为了避免传统控制律固有的奇异性，在设计中引入了光滑双曲正切函数。此外，在自适应动态曲面控制结构中引入了复合学习框架，实现了预定义时间误差收敛。基于lyapunov的分析证实了闭环系统的半全局一致预定义时有界性。仿真结果验证了所提控制策略的有效性和鲁棒性。

引用次数: 0

Finite-time adaptive tracking control for uncertain nonlinear systems 不确定非线性系统的有限时间自适应跟踪控制

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-11-10 DOI: 10.1016/j.ejcon.2025.101410

Guang-Xin Zhong , Li-Yao Wang , Yue Long , Jian Li , Zhen-Xing Zhang , Xiao-Qi Zhao

This article investigates a finite-time adaptive tracking control problem for uncertain nonlinear systems. The uncertainty is modeled as an unknown time-varying parameter, which is further coupled with the function characterizing the system nonlinear behavior. By constructing a novel uncertainty-based operator, a mixed upper/lower bound-dependent stable time interval is estimated. This means that the relationship between system internal uncertainty and finite stable time is established. Next, a command filter is designed, which generates the virtual output to replace the differentiation existing in the process of constructing the virtual input. This removes the much repeated differential operation during adaptive control algorithm design phase and simplifies the corresponding controller structure. Finally, based on a bound-dependent Lagrange operator, a novel finite-time adaptive tracking controller is designed. The controller integrates with a compensation mechanism, which leads to better tracking performance in a finite time. Experimental results with a one-link manipulator with motor dynamics are provided to verify the effectiveness of the proposed scheme.

研究不确定非线性系统的有限时间自适应跟踪控制问题。将不确定性建模为未知时变参数，并与表征系统非线性行为的函数耦合。通过构造一种新的基于不确定性的算子，估计出一个混合上下界相关的稳定时间区间。这意味着建立了系统内部不确定性与有限稳定时间之间的关系。其次，设计命令滤波器，生成虚拟输出，以取代构造虚拟输入过程中存在的微分。这消除了自适应控制算法设计阶段大量重复的微分运算，简化了相应的控制器结构。最后，基于有界相关的拉格朗日算子，设计了一种新的有限时间自适应跟踪控制器。该控制器集成了补偿机制，在有限时间内具有更好的跟踪性能。最后给出了带电机动力学的单连杆机械手的实验结果，验证了所提方案的有效性。

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引用次数: 0

Average-based aperiodic intermittent control for secure synchronization of antagonistic networks 对抗网络安全同步的基于平均的非周期间歇控制

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-11-08 DOI: 10.1016/j.ejcon.2025.101411

Lingzhong Zhang , Jianquan Lu , Bowen Li , Jürgen Kurths

This paper studies the bipartite mean-square bounded synchronization of coupled neural networks (NNs) under anti-attack aperiodic intermittent control (AIC). A deception attack model targeting controller–actuator channels in antagonistically coupled NNs is proposed, addressing integrity breaches in communication channels and malicious command injections via intermittent access points. By incorporating averaging into intermittent control, the proposed strategy substantially enhances synchronization robustness of antagonistic networks against deceptive actuators. Through rigorous analysis employing the average AIC interval methodology, some sufficient conditions ensuring bipartite mean-square bounded synchronization for the coupled NNs are established, and the traditional strict upper/lower bounds on AIC width parameters are relaxed. To ensure the synchronization errors remain within the prescribed upper bound, the coupling strength, attack probability and the average AIC width are co-designed. Elastic interval boundary conditions for aperiodic control are derived via an average control duration analysis. Finally, numerical examples are given to demonstrate the derived results.

研究了抗攻击非周期间歇控制下耦合神经网络的二部均方有界同步问题。提出了一种针对拮抗耦合神经网络中控制器-执行器通道的欺骗攻击模型，解决了通信通道完整性破坏和通过间歇接入点注入恶意命令的问题。通过在间歇控制中加入平均，所提出的策略大大提高了对抗网络对欺骗性致动器的同步鲁棒性。通过对平均AIC区间方法的严密分析，建立了保证耦合神经网络二部均方有界同步的充分条件，放宽了传统的AIC宽度参数严格的上下界。为了保证同步误差在规定的上限内，对耦合强度、攻击概率和平均AIC宽度进行了协同设计。通过对平均控制时间的分析，导出了非周期控制的弹性区间边界条件。最后，通过数值算例对所得结果进行了验证。

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引用次数: 0

Bias correction and instrumental variables for direct data-driven model-reference control 偏差校正和仪器变量直接数据驱动的模型参考控制

IF 2.6 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

European Journal of Control

Pub Date : 2025-11-01 DOI: 10.1016/j.ejcon.2025.101327

Manas Mejari , Valentina Breschi , Milad Banitalebi Dehkordi , Simone Formentin , Dario Piga

Managing noisy data is a central challenge in direct data-driven control design. We propose an approach for synthesizing model-reference controllers for linear time-invariant (LTI) systems using noisy state-input data, employing novel noise mitigation techniques. We demonstrate that data-based covariance parameterization of the controller enables to incorporate bias-correction and instrumental variable techniques. This reduces measurement noise effects as data volume increases. The number of decision variables remains independent of dataset size, making this method scalable to large datasets. The approach’s effectiveness is demonstrated with a numerical example.

管理噪声数据是直接数据驱动控制设计的核心挑战。我们提出了一种利用噪声状态输入数据合成线性时不变（LTI）系统的模型参考控制器的方法，采用了新的噪声抑制技术。我们证明了基于数据的控制器协方差参数化能够结合偏差校正和工具变量技术。随着数据量的增加，这减少了测量噪声的影响。决策变量的数量与数据集大小无关，使该方法可扩展到大型数据集。通过数值算例验证了该方法的有效性。

引用次数: 0

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