{"title":"Mean-field social optimization for linear–quadratic Markov switching systems with Poisson jumps","authors":"Ruimin Xu , Jingyu Zhang , Kaiyue Dong , Haiyang Wang","doi":"10.1016/j.ejcon.2025.101356","DOIUrl":"10.1016/j.ejcon.2025.101356","url":null,"abstract":"<div><div>This paper investigates social optima for linear–quadratic-Gaussian (LQG) games of stochastic mean-field Markov regime-switching systems with jump diffusion processes, where the individual agents of the system are coupled via individual state dynamics and cost functionals. A verification theorem in the form of maximum principle is established, specifying the sufficient conditions for optimality. A set of decentralized strategies is designed according to the feedback representation of optimal control. The decentralized strategies are proved to be asymptotically social optimal. As an illustration, a numerical example is provided to show the consistency of the mean-field estimation and the influence of the population’s collective behaviors.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101356"},"PeriodicalIF":2.6,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Milad Banitalebi Dehkordi, Marco Forgione, Dario Piga
{"title":"Uncertainty quantification in neural state-space models: Applications for experiment design and uncertainty-aware MPC","authors":"Milad Banitalebi Dehkordi, Marco Forgione, Dario Piga","doi":"10.1016/j.ejcon.2025.101359","DOIUrl":"10.1016/j.ejcon.2025.101359","url":null,"abstract":"<div><div>This paper addresses the problem of uncertainty quantification in neural state-space models from a Bayesian perspective. The posterior distribution over the neural network parameters is derived and approximated using the Laplace method, resulting in a Gaussian approximation of the model’s predictive distribution. Based on the predictive distribution, we introduce an uncertainty index that quantifies the model’s confidence over any possible input sequence, enabling the detection of out-of-distribution regimes. This index is then leveraged in two applications: (i) experiment design for the identification of state-space models, and (ii) model predictive control under epistemic uncertainty.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101359"},"PeriodicalIF":2.6,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Non-overshooting quasi-continuous sliding mode control for second-order systems","authors":"Michael Ruderman , Denis Efimov","doi":"10.1016/j.ejcon.2025.101355","DOIUrl":"10.1016/j.ejcon.2025.101355","url":null,"abstract":"<div><div>This paper proposes a nonlinear sliding mode state feedback controller for perturbed second-order systems. In analogy to a linear proportional-derivative (PD) feedback control, the proposed nonlinear scheme uses the output of interest and its time derivative. The control has only one free design parameter, and the closed-loop system is shown to possess uniform boundedness and finite-time convergence of trajectories in the presence of matched disturbances. We derive a strict Lyapunov function for the closed-loop control system with a bounded exogenous perturbation, and use it for both, the control parameter tuning and analysis of the finite-time convergence. The essential features of the proposed control law is non-overshooting despite the unknown dynamic disturbances and the continuous control action during the convergence to zero equilibrium. Apart from the numerical results, a revealing experimental example is also shown in favor of the proposed control and in comparison with PD and sub-optimal nonlinear damping regulators.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101355"},"PeriodicalIF":2.6,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Are Artificial Neural Networks suitable for data-driven moment matching?","authors":"Matteo Scandella , Davide Previtali , Alessio Moreschini","doi":"10.1016/j.ejcon.2025.101360","DOIUrl":"10.1016/j.ejcon.2025.101360","url":null,"abstract":"<div><div>We investigate the use of artificial neural networks in the context of data-driven moment matching for nonlinear systems, comparing it with state-of-the-art approaches that rely on regularized kernel methods or least squares. We propose a novel neural network model that shares the properties of the moment function of a nonlinear system, which can be learned by means of surrogate-based black-box optimization methods (such as Bayesian optimization). To validate the proposed approach, we conduct an extensive simulation analysis of the method on two benchmark model reduction problems, employing different settings and comparing with state-of-the-art methods. This investigation suggests that neural networks are a suitable and promising approach for data-driven moment matching, and they appear to show comparable performance to state-of-the-art methods based on regularized kernel methods.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101360"},"PeriodicalIF":2.6,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integral sliding mode smooth control for joint position tracking of position servo-actuated robot manipulators","authors":"Luis Pantoja-Garcia , Gabriela Zepeda","doi":"10.1016/j.ejcon.2025.101351","DOIUrl":"10.1016/j.ejcon.2025.101351","url":null,"abstract":"<div><div>Designing robust control systems for robotic manipulators, especially for trajectory tracking, is an ongoing research focus due to their growing use in various industries. Developing effective control algorithms for these systems also presents a significant theoretical challenge. However, control designs are often based on the implicit and unrealistic assumption of ideal, memoryless torque actuators, whereas in practice, robots are equipped with position servo actuators that receive position commands as input. This discrepancy often goes unnoticed during analysis and implementation. To address this shortcoming, this paper proposes an integral sliding mode control approach for motion tracking of position servo-actuated robotic manipulators in joint space, where the inputs are the desired position signals received by the actuators. The robot’s mechanical dynamics and servo parameters are assumed to be unknown, yielding a model-free controller. A notable feature of the proposed approach is that the control action is smooth, effectively avoiding the harmful chattering phenomenon. We ensure that the control objective is achieved even in the presence of unknown bounded and continuous disturbances. Simulations of a robot manipulator equipped with position servo actuators demonstrate the effectiveness of the proposed control strategy.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101351"},"PeriodicalIF":2.6,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hebertt Sira-Ramírez , Mario Andrés Aguilar-Orduña , Brian Camilo Gómez-León
{"title":"An invariance approach for sliding mode control design in nonlinear switched systems","authors":"Hebertt Sira-Ramírez , Mario Andrés Aguilar-Orduña , Brian Camilo Gómez-León","doi":"10.1016/j.ejcon.2025.101344","DOIUrl":"10.1016/j.ejcon.2025.101344","url":null,"abstract":"<div><div>This article presents a method for synthesizing sliding mode controllers in Single Input Single Output (SISO) switched nonlinear systems. The method, called the <em>invariance control method</em>, utilizes the invariance condition associated with each constant level set of the sliding surface coordinate function. It decomposes the SM control scheme into two parts: a smooth invariance feedback controller and a Delta-Sigma modulator. The smooth invariance feedback controller represents the equivalent control in a specific case, while the Delta-Sigma modulator provides the required binary-valued input signal to the switched plant based on the output of the invariance controller. The method can be applied to differentially flat systems with switched inputs, using linear, self-compensating sliding surface coordinate functions. The approach aligns with the Active Disturbance Rejection Control scheme for the average system but incorporates a Delta-Sigma modulator. The article showcases the method’s effectiveness through digital computer simulations and laboratory experiments with non-trivial application examples.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101344"},"PeriodicalIF":2.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Model predictive control of switched affine systems with dwell time constraints—Efficient formulation, approximation and embedded implementation","authors":"Faiq Ghawash , Morten Hovd , Brad Schofield","doi":"10.1016/j.ejcon.2025.101347","DOIUrl":"10.1016/j.ejcon.2025.101347","url":null,"abstract":"<div><div>In this work, we study the problem of designing a model predictive control (MPC) strategy for switched affine systems with dwell time constraints. We show that the task of simultaneous determination of the optimal operational mode and actuator inputs can be formulated within the generalized disjunctive programming (GDP) framework and highlight its computational advantages over traditional techniques. Although GDP provides an efficient parametrization of the associated mixed integer program, the combinatorial nature of the problem might require a large computational time limiting its applicability in real time scenarios. To this end, we propose a framework based on the multitask learning paradigm to approximate the solution of mixed integer MPC for switched affine systems. We also provide a computational method based on the offline solution of a mixed integer linear program to overapproximate the reachable sets of the closed loop system that helps to analyze the safety and stability of the system under the influence of the learned controller. Once trained offline, the resulting controller results in a solver free approach well suited for implementation on a resource constrained embedded hardware. Several illustrative examples are provided to show the efficacy of the proposed approach.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101347"},"PeriodicalIF":2.6,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sliding Mode Control with exponential and finite-time reaching laws in heading control for autonomous sailboats","authors":"Peerayot Sanposh , Yodyium Tipsuwan , Nattakit Techajaroonjit","doi":"10.1016/j.ejcon.2025.101345","DOIUrl":"10.1016/j.ejcon.2025.101345","url":null,"abstract":"<div><div>This paper presents a model-based nonlinear control approach using Sliding Mode Control (SMC) and a data fitting approach to enhance the practical implementation of heading control for autonomous sailboats. Two controllers are proposed based on the exponential reaching law and the finite-time reaching law, ensuring Lyapunov stability with distinct convergence characteristics. To approximate the lift and drag coefficients in the sailboat dynamic model, a least squares fitting approach is utilized to reduce the number of tuning parameters. In addition, robustness validation considers the case in which only partial lift and drag coefficient data are available. These key contributions enable practical implementation without full system identification. The effectiveness of the proposed controllers is evaluated through simulations, focusing on tacking and jibing maneuver scenarios under external disturbances and model uncertainties. Simulation results confirm the robustness of the proposed controllers and demonstrate that they successfully stabilize the heading error, achieve a trade-off between settling time and overshoot, and outperform a baseline controller during the jibing maneuver scenario.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101345"},"PeriodicalIF":2.6,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"State estimation for discrete-event systems with reliable states under sequential attacks","authors":"Yonghong Luo, Shaowen Miao, Aiwen Lai","doi":"10.1016/j.ejcon.2025.101349","DOIUrl":"10.1016/j.ejcon.2025.101349","url":null,"abstract":"<div><div>Cyber–physical systems are crucial in industry and are often modeled as discrete-event systems for analysis. One major concern is that the communication in cyber–physical systems is susceptible to three types of attacks: deletions, insertions, and substitutions. To prevent communication signals from being tampered with, communication protection can be used in particular states referred to as reliable states. In this paper, the state estimation problem for discrete-event systems with reliable states under sequential attacks is formulated and solved. Additionally, under sequential attacks, we construct a tampered reliable automaton, derived from the original system, to achieve state estimation efficiently. Finally, we analyze the impact of reliable states on the opacity of the tampered reliable automaton when an original automaton is opaque.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101349"},"PeriodicalIF":2.6,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of cascaded PDE-ODE observers for LTI systems with numerical differentiators as fictitious sensors with distributed delay","authors":"Florian Meiners , Amine Othmane , Jürgen Adamy","doi":"10.1016/j.ejcon.2025.101353","DOIUrl":"10.1016/j.ejcon.2025.101353","url":null,"abstract":"<div><div>Unmeasured states of an observable LTI system without sensor delay can be determined by use of a state observer or calculated directly from the input, the output, and their successive time derivatives. The inherent ill-posedness of numerical differentiation renders the latter approach unsuitable for most control applications. Design objectives like the need to balance convergence rates and steady-state noise suppression, on the other hand, pose significant challenges for state observation. This work proposes a systematic framework for the combination of numerical differentiation and output error injection to leverage benefits of both methods. By interpreting estimates of the output derivatives of an LTI system without sensor delay as additional, but delayed, outputs, a cascaded PDE-ODE formulation of the augmented system is derived. In it, the derivative estimates, which are treated as readings from fictitious sensors, are modeled by transport equations. An observer for the resulting system is developed. We prove that additional information inferred from output derivatives improves observability properties of the underlying system in terms of the observability Gramian. Moreover, incorporating the output derivatives introduces additional degrees of freedom to the design. We show how such degrees of freedom can be exploited; in particular, they can be used to improve noise attenuation due to a reduction of the injection gains. An analysis of the observer for the PDE-ODE cascade and a comparison to the Luenberger observer are provided. The efficacy of the proposed method is illustrated experimentally.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"85 ","pages":"Article 101353"},"PeriodicalIF":2.6,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}