European Journal of Control最新文献

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A stability condition for online feedback optimization without timescale separation 无时间尺度分离的在线反馈优化稳定性条件

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.2025.101308

Mattia Bianchi, Florian Dörfler

Online Feedback Optimization (OFO) is a control approach to drive a dynamical plant to an optimal steady state. By interconnecting optimization algorithms with real-time plant measurements, OFO provides all the benefits of feedback control, yet without requiring exact knowledge of plant dynamics for computing a setpoint. On the downside, existing stability guarantees for OFO require the controller to evolve on a sufficiently slower timescale than the plant, possibly affecting transient performance and responsiveness to disturbances. In this paper, we prove that, under suitable conditions, OFO ensures stability without any timescale separation. In particular, the condition we propose is independent of the time constant of the plant, hence it is scaling-invariant. Our analysis leverages a composite Lyapunov function, which is the

max

of plant-related and controller-related components. We corroborate our theoretical results with numerical examples.

在线反馈优化（OFO）是一种使动态对象达到最优稳态的控制方法。通过将优化算法与实时工厂测量相连接，OFO提供了反馈控制的所有好处，但不需要精确的工厂动态知识来计算设定点。缺点是，OFO现有的稳定性保证要求控制器在比工厂更慢的时间尺度上进化，这可能会影响瞬态性能和对干扰的响应。在本文中，我们证明了在适当的条件下，OFO在没有时间尺度分离的情况下保证了稳定性。特别地，我们提出的条件与被测对象的时间常数无关，因此它是标度不变的。我们的分析利用了一个复合Lyapunov函数，它是与植物相关和与控制器相关的组件的最大值。我们用数值算例证实了理论结果。

引用次数: 0

Closed-loop performance optimization of model predictive control with robustness guarantees 具有鲁棒性保证的模型预测控制闭环性能优化

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.2025.101319

Riccardo Zuliani , Efe C. Balta , John Lygeros

Model mismatch and process noise are two frequently occurring phenomena that can drastically affect the performance of model predictive control (MPC) in practical applications. We propose a principled way to tune the cost function and the constraints of linear MPC schemes to improve the closed-loop performance and robust constraint satisfaction on uncertain nonlinear dynamics with additive noise. The tuning is performed using a novel MPC tuning algorithm based on backpropagation developed in our earlier work. Using the scenario approach, we provide probabilistic bounds on the likelihood of closed-loop constraint violation over a finite horizon. We showcase the effectiveness of the proposed method on linear and nonlinear simulation examples.

在实际应用中，模型失配和过程噪声是影响模型预测控制性能的两种常见现象。我们提出了一种原则性的方法来调整线性MPC方案的成本函数和约束，以提高具有加性噪声的不确定非线性动力学的闭环性能和鲁棒约束满意度。调优是使用我们早期工作中开发的基于反向传播的新型MPC调优算法进行的。利用情景方法，我们给出了在有限视界上闭环约束违反的可能性的概率界。我们在线性和非线性仿真实例上展示了该方法的有效性。

引用次数: 0

A system parametrization for direct data-driven analysis and control with error-in-variables 用于直接数据驱动分析和变量误差控制的系统参数化

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.2025.101307

Felix Brändle, Frank Allgöwer

In this paper, we present a new parametrization to perform direct data-driven analysis and controller synthesis for the error-in-variables case. To achieve this, we employ the Sherman–Morrison–Woodbury formula to transform the problem into a linear fractional transformation with unknown measurement errors and disturbances as uncertainties. For bounded uncertainties, we apply robust control techniques to derive a guaranteed upper bound on the

H_{2}

-norm of the unknown true system. To this end, a single semidefinite program needs to be solved, with complexity that is independent of the amount of data. Furthermore, we exploit the signal-to-noise ratio to provide a data-dependent condition, that characterizes whether the proposed parametrization can be employed. The modular formulation allows to extend this framework to controller synthesis with different performance criteria, input–output settings, and various system properties. Finally, we validate the proposed approach through a numerical example.

在本文中，我们提出了一种新的参数化方法，用于对变量误差情况进行直接数据驱动分析和控制器综合。为了实现这一点，我们采用Sherman-Morrison-Woodbury公式将问题转换为具有未知测量误差和干扰作为不确定性的线性分数变换。对于有界不确定性，我们应用鲁棒控制技术推导出未知真系统h2 -范数的保证上界。为此，需要解决单个半确定程序，其复杂性与数据量无关。此外，我们利用信噪比来提供一个与数据相关的条件，该条件表征了所提出的参数化是否可以采用。模块化配方允许将该框架扩展到具有不同性能标准、输入输出设置和各种系统属性的控制器合成。最后，通过一个数值算例验证了该方法的有效性。

引用次数: 0

A continuification-based control solution for large-scale shepherding 一种基于连续的大规模牧羊控制解决方案

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.2025.101324

Beniamino Di Lorenzo , Gian Carlo Maffettone , Mario di Bernardo

In this paper, we address the large-scale shepherding control problem using a density control strategy based on continuification. We consider a scenario in which a large group of follower agents (targets) must be confined within a designated goal region through indirect interactions with a controllable set of leader agents (herders). Our approach transforms the microscopic agent-based dynamics into a macroscopic continuum model. This formulation enables efficient, scalable control design for the herders’ behavior, with guarantees of global convergence. The approach is validated through comprehensive numerical simulations and novel mixed-reality experiments integrating physical and virtual agents, demonstrating both its effectiveness and practical applicability.

本文采用一种基于连续化的密度控制策略来解决大规模牧羊控制问题。我们考虑一个场景，在这个场景中，一大群跟随智能体（目标）必须通过与一组可控的领导智能体（牧人）的间接交互而被限制在指定的目标区域内。我们的方法将微观主体动力学转化为宏观连续体模型。这个公式使有效的，可扩展的控制设计牧人的行为，并保证全局收敛。通过综合数值模拟和新型混合现实实验验证了该方法的有效性和实用性。

引用次数: 0

Derivative-free Kalman filtering for a six-wheeled rover 六轮漫游者的无导数卡尔曼滤波

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.2025.101334

Beatrice M. Bălăceanu , Florin Stoican , Bogdan D. Ciubotaru , Ionela Prodan

The aim of this paper is to provide a Derivative-free Kalman Filter (DKF) for a six-wheeled rover, as an alternative to the classical Kalman Filters. The DKF removes the risks which the Extended Kalman Filter (EKF), based on the computation of Jacobians, pose when implemented on platforms with limited numerical precision. It is also more computationally efficient than the Unscented Kalman filters, while retaining similar performance. The DKF is designed for an Ackermann steered six-wheeled rover which has nonlinear, coupled longitudinal and lateral dynamics. Starting from the first principles of the two axle car, we derive the rover’s mathematical model, which we then express through a flat-output representation. Using the resulting Brunovsky form, we provide both a position estimate (via the DKF) and a control module (a reference tracking variation). The model and its ancillary blocks are tested in simulation to validate the flat representation’s consistency and the performance of the navigation and control actions.

本文的目的是为六轮漫游车提供一种无导数卡尔曼滤波器（DKF），作为经典卡尔曼滤波器的替代方案。DKF消除了基于雅可比矩阵计算的扩展卡尔曼滤波器（EKF）在数值精度有限的平台上实现时所带来的风险。它也比Unscented卡尔曼滤波器计算效率更高，同时保持相似的性能。DKF是针对一种具有非线性、纵向和横向耦合动力学的阿克曼转向六轮探测车而设计的。从两轴小车的基本原理出发，推导出了漫游车的数学模型，并将其用平面输出表示出来。使用得到的布鲁诺夫斯基形式，我们提供了位置估计（通过DKF）和控制模块（参考跟踪变化）。对模型及其附属块进行了仿真测试，验证了平面表示的一致性以及导航和控制动作的性能。

引用次数: 0

Observer design conditions for piecewise linear systems with known and unknown inputs 具有已知和未知输入的分段线性系统的观测器设计条件

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.2025.101321

Manuel Mera , Rosane Ushirobira , Denis Efimov , Francisco Javier Bejarano

This paper presents sufficient reconstructability and observability conditions for piecewise linear systems affected by known and unknown inputs. Based on these conditions, an observer design using a High Order Sliding Mode (HOSM) differentiator is proposed to estimate both the continuous and discrete states. Additionally, numerical examples and simulations are given to explain and illustrate the results.

本文给出了受已知和未知输入影响的分段线性系统的充分可重构性和可观测性条件。在此基础上，提出了一种基于高阶滑模（HOSM）微分器的观测器设计，用于估计连续状态和离散状态。此外，还给出了数值算例和模拟来解释和说明结果。

引用次数: 0

From microscopic driver models to macroscopic PDEs in ring road traffic dynamics 从微观驾驶员模型到环路交通动力学的宏观偏微分方程

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.2025.101364

S. Fueyo, C. Canudas de Wit

In this paper, using a continuation method (Nikitin and Canudas-de Wit, 2022), we provide a simple procedure to derive macroscopic models from second order ordinary differential equations modeling individual vehicles moving on a ring. In particular, the result is applied to classical traffic models such as the optimal velocity follow the leader (OV-FTL) models, the intelligent driver model (IDM) or delayed driver models and we are able to modelize the macroscopic behavior of the drivers through a 2 × 2 partial differential equations whose variables are the density of the traffic and the speed of the vehicles. The paper concludes with open questions regarding stability and microscopic control design.

在本文中，使用延拓方法（Nikitin和Canudas-de Wit， 2022），我们提供了一个简单的程序，从模拟在环上移动的单个车辆的二阶常微分方程中导出宏观模型。特别是，将结果应用于经典的交通模型，如最优速度跟随（OV-FTL）模型、智能驾驶员模型（IDM）或延迟驾驶员模型，我们能够通过以交通密度和车辆速度为变量的2 × 2偏微分方程来建模驾驶员的宏观行为。文章最后提出了稳定性和微观控制设计方面的开放性问题。

引用次数: 0

Discrete-time prescribed performance control with time-varying transmission intervals 具有时变传输间隔的离散时间规定性能控制

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.2025.101365

Lampros N. Bikas, Konstantinos M. Vervelithanos, George A. Rovithakis

This paper extends the prescribed performance control (PPC) methodology to discrete-time control with time-varying transmission intervals. Starting from a continuous-time PPC scheme that enforces pre-specified, user-defined performance bounds on output tracking errors, we develop a dynamic control protocol that determines sampling instants in real-time. This approach preserves closed-loop stability and output tracking performance while allowing transmission intervals to vary according to the current error distance from the performance bounds. By adapting the sampling times accordingly, our method reduces sampling frequency and improves system efficiency and reliability. Furthermore, we show that stricter performance requirements result in smaller transmission intervals, whereas relaxed requirements permit larger ones. Theoretical analysis and simulation results verify the effectiveness of the proposed approach.

本文将规定的性能控制方法推广到具有时变传输间隔的离散时间控制。从连续时间PPC方案开始，该方案强制执行预先指定的、用户自定义的输出跟踪误差性能界限，我们开发了一个动态控制协议，实时确定采样时刻。这种方法保留了闭环稳定性和输出跟踪性能，同时允许传输间隔根据当前与性能界限的误差距离变化。通过对采样时间的调整，降低了采样频率，提高了系统的效率和可靠性。此外，我们表明严格的性能要求导致更小的传输间隔，而宽松的要求允许更大的传输间隔。理论分析和仿真结果验证了该方法的有效性。

引用次数: 0

Derivative-free data-driven control of continuous-time linear time-invariant systems 连续时间线性定常系统的无导数数据驱动控制

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.2025.101309

Alessandro Bosso , Marco Borghesi , Andrea Iannelli , Giuseppe Notarstefano , Andrew R. Teel

This paper develops a method for data-driven stabilization of continuous-time linear time-invariant systems with theoretical guarantees and no need for signal derivatives. The framework is based on linear matrix inequalities (LMIs) and illustrated in the state-feedback and single-input single-output output-feedback scenarios. Similar to discrete-time approaches, we rely solely on input and state/output measurements. In particular, we avoid differentiation by employing low-pass filters of the measured signals that, rather than approximating the derivatives, reconstruct a non-minimal realization of the plant. With access to the filter states and their derivatives, we can solve LMIs derived from sample batches of the available signals to compute a dynamic controller that stabilizes the plant. The effectiveness of the approach is showcased via numerical examples.

本文提出了一种具有理论保证且不需要信号导数的连续时间线性定常系统的数据驱动镇定方法。该框架基于线性矩阵不等式（lmi），并在状态反馈和单输入单输出输出反馈场景中进行了说明。与离散时间方法类似，我们仅依赖于输入和状态/输出测量。特别是，我们通过采用测量信号的低通滤波器来避免微分，而不是近似导数，重建植物的非最小实现。通过对滤波器状态及其导数的访问，我们可以求解由可用信号的样本批次导出的lmi，以计算稳定对象的动态控制器。通过数值算例验证了该方法的有效性。

引用次数: 0

FJ-MM: Friedkin–Johnsen opinion dynamics model with memory and higher-order neighbors FJ-MM：具有记忆和高阶邻域的Friedkin-Johnsen意见动态模型

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.2025.101306

Roberta Raineri, Lorenzo Zino, Anton Proskurnikov

The Friedkin–Johnsen (FJ) model has been extensively validated across social science, systems and control, game theory, and algorithmic research. We introduce an advanced generalization — termed the FJ-MM model — that incorporates memory effects and multi-hop influence. This extension allows agents to naturally integrate both current and past opinions at each iteration. We analyze the stability and equilibrium properties of the FJ-MM model, demonstrating that they can be derived from those of a standard FJ model with an appropriately modified influence matrix. We examine the convergence rate of the FJ-MM model and demonstrate that, as can be expected, the time lags introduced by memory and higher-order neighbor influences result in slower convergence. Numerical results illustrate that memory and multi-hop influence reshape the final opinion landscape, e.g., by reducing polarization.

弗里德金-约翰森（FJ）模型在社会科学、系统与控制、博弈论和算法研究中得到了广泛的验证。我们引入了一种先进的泛化-称为FJ-MM模型-它结合了记忆效应和多跳影响。这个扩展允许代理在每次迭代中自然地集成当前和过去的意见。我们分析了FJ- mm模型的稳定性和平衡特性，证明了它们可以通过适当修改影响矩阵从标准FJ模型的稳定性和平衡特性中导出。我们检查了FJ-MM模型的收敛速度，并证明，正如预期的那样，由记忆和高阶邻居影响引入的时间滞后导致较慢的收敛速度。数值结果表明，记忆和多跳影响重塑了最终的意见格局，例如，通过减少极化。

引用次数: 0

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