Pub Date : 2025-12-02DOI: 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.
{"title":"Continuous trajectory planning for non-convex utility functions using hybrid optimization","authors":"He Hao , Daniel Silvestre , Carlos Silvestre","doi":"10.1016/j.ejcon.2025.101425","DOIUrl":"10.1016/j.ejcon.2025.101425","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"87 ","pages":"Article 101425"},"PeriodicalIF":2.6,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145791112","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}
Pub Date : 2025-12-01DOI: 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.
{"title":"Approximations of the set of trajectories, attainable sets and integral funnel of the control system with mixed constraints on the control functions","authors":"Nesir Huseyin , Anar Huseyin , Khalik G. Guseinov , Vladimir N. Ushakov","doi":"10.1016/j.ejcon.2025.101422","DOIUrl":"10.1016/j.ejcon.2025.101422","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"87 ","pages":"Article 101422"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738136","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}
Pub Date : 2025-12-01DOI: 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.
{"title":"Asymptotic boundedness and exponential stability of neutral stochastic functional differential equations with unbounded delay","authors":"Wei Mao , Xiaomu Ling , Jie He , Fuke Wu , Xuerong Mao","doi":"10.1016/j.ejcon.2025.101423","DOIUrl":"10.1016/j.ejcon.2025.101423","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"87 ","pages":"Article 101423"},"PeriodicalIF":2.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665378","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}
Pub Date : 2025-11-27DOI: 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.
{"title":"DREM-based predefined-time adaptive learning control for nonlinear systems with actuator faults and input delay","authors":"Mohamed Kharrat","doi":"10.1016/j.ejcon.2025.101426","DOIUrl":"10.1016/j.ejcon.2025.101426","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"87 ","pages":"Article 101426"},"PeriodicalIF":2.6,"publicationDate":"2025-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738181","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}
Pub Date : 2025-11-10DOI: 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.
{"title":"Finite-time adaptive tracking control for uncertain nonlinear systems","authors":"Guang-Xin Zhong , Li-Yao Wang , Yue Long , Jian Li , Zhen-Xing Zhang , Xiao-Qi Zhao","doi":"10.1016/j.ejcon.2025.101410","DOIUrl":"10.1016/j.ejcon.2025.101410","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101410"},"PeriodicalIF":2.6,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519536","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}
Pub Date : 2025-11-08DOI: 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.
{"title":"Average-based aperiodic intermittent control for secure synchronization of antagonistic networks","authors":"Lingzhong Zhang , Jianquan Lu , Bowen Li , Jürgen Kurths","doi":"10.1016/j.ejcon.2025.101411","DOIUrl":"10.1016/j.ejcon.2025.101411","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101411"},"PeriodicalIF":2.6,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571524","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}
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.
{"title":"Bias correction and instrumental variables for direct data-driven model-reference control","authors":"Manas Mejari , Valentina Breschi , Milad Banitalebi Dehkordi , Simone Formentin , Dario Piga","doi":"10.1016/j.ejcon.2025.101327","DOIUrl":"10.1016/j.ejcon.2025.101327","url":null,"abstract":"<div><div>Managing noisy data is a central challenge in direct data-driven control design. We propose an approach for synthesizing model-reference controllers for <em>linear time-invariant</em> (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.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101327"},"PeriodicalIF":2.6,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145645411","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}
Pub Date : 2025-11-01DOI: 10.1016/j.ejcon.2025.101323
Yun Li , Jicheng Shi , Colin N. Jones , Neil Yorke-Smith , Tamas Keviczky
Noise pollution from heat pumps (HPs) has been an emerging concern to their broader adoption, especially in densely populated areas. This paper explores a model predictive control (MPC) approach for climate control of buildings, aimed at minimizing the noise nuisance generated by HPs. By exploiting a piecewise linear approximation of HP noise patterns and assuming linear building thermal dynamics, the proposed design can be generalized to handle various HP acoustic patterns with mixed-integer linear programming (MILP). Additionally, two computationally efficient options for defining the noise cost function in the proposed MPC design are discussed. Numerical experiments on a high-fidelity building simulator are performed to demonstrate the viability and effectiveness of the proposed design. Simulation results show that minimizing the excess of HP noise over ambient noise is effective in mitigating the HP noise nuisance. Further, compared with the conventional MPC-based building climate control scheme, the proposed approach can effectively reduce the HP noise pollution with only a minor energy cost increase.
{"title":"Model predictive building climate control for mitigating heat pump noise pollution","authors":"Yun Li , Jicheng Shi , Colin N. Jones , Neil Yorke-Smith , Tamas Keviczky","doi":"10.1016/j.ejcon.2025.101323","DOIUrl":"10.1016/j.ejcon.2025.101323","url":null,"abstract":"<div><div>Noise pollution from heat pumps (HPs) has been an emerging concern to their broader adoption, especially in densely populated areas. This paper explores a model predictive control (MPC) approach for climate control of buildings, aimed at minimizing the noise nuisance generated by HPs. By exploiting a piecewise linear approximation of HP noise patterns and assuming linear building thermal dynamics, the proposed design can be generalized to handle various HP acoustic patterns with mixed-integer linear programming (MILP). Additionally, two computationally efficient options for defining the noise cost function in the proposed MPC design are discussed. Numerical experiments on a high-fidelity building simulator are performed to demonstrate the viability and effectiveness of the proposed design. Simulation results show that minimizing the excess of HP noise over ambient noise is effective in mitigating the HP noise nuisance. Further, compared with the conventional MPC-based building climate control scheme, the proposed approach can effectively reduce the HP noise pollution with only a minor energy cost increase.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101323"},"PeriodicalIF":2.6,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145645417","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}
Pub Date : 2025-11-01DOI: 10.1016/j.ejcon.2025.101368
Feng-Yu Yue, Daniel Zelazo
This work deals with the output consensus problems for multi-agent systems over balanced digraphs. While passivity-based approaches are widely used for analyzing undirected consensus protocols, we show that they are generally not applicable to the directed linear consensus protocol. To address this limitation, we propose a general approach that enables a passivity-based analysis for network systems with directed couplings. Then, we mitigate the complexity introduced by nonlinearities and directed interconnections by reformulating the general output consensus problem as a convergence analysis on a submanifold. Within this framework, we further focus on the stabilization problem, a specific form of the output consensus problem, and establish a sufficient passivity-based condition for stabilizing multi-agent systems over balanced digraphs. The results are supported by a numerical example.
{"title":"A passivity analysis for nonlinear consensus on balanced digraphs","authors":"Feng-Yu Yue, Daniel Zelazo","doi":"10.1016/j.ejcon.2025.101368","DOIUrl":"10.1016/j.ejcon.2025.101368","url":null,"abstract":"<div><div>This work deals with the output consensus problems for multi-agent systems over balanced digraphs. While passivity-based approaches are widely used for analyzing undirected consensus protocols, we show that they are generally not applicable to the directed linear consensus protocol. To address this limitation, we propose a general approach that enables a passivity-based analysis for network systems with directed couplings. Then, we mitigate the complexity introduced by nonlinearities and directed interconnections by reformulating the general output consensus problem as a convergence analysis on a submanifold. Within this framework, we further focus on the stabilization problem, a specific form of the output consensus problem, and establish a sufficient passivity-based condition for stabilizing multi-agent systems over balanced digraphs. The results are supported by a numerical example.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101368"},"PeriodicalIF":2.6,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145645535","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}
Pub Date : 2025-11-01DOI: 10.1016/j.ejcon.2025.101300
Zixing Wang, Yi Zhang, Fulvio Forni
We tackle the problem of providing closed-loop stability guarantees with a scalable data-driven design. We combine virtual reference feedback tuning with dissipativity constraints on the controller for closed-loop stability. The constraints are formulated as a set of linear inequalities in the frequency domain. This leads to a convex problem that is scalable with respect to the length of the data and the complexity of the controller. An extension of virtual reference feedback tuning to include disturbance dynamics is also discussed. The proposed data-driven control design is illustrated by a soft gripper impedance control example.
{"title":"Dissipative iFIR filters for data-driven design","authors":"Zixing Wang, Yi Zhang, Fulvio Forni","doi":"10.1016/j.ejcon.2025.101300","DOIUrl":"10.1016/j.ejcon.2025.101300","url":null,"abstract":"<div><div>We tackle the problem of providing closed-loop stability guarantees with a scalable data-driven design. We combine virtual reference feedback tuning with dissipativity constraints on the controller for closed-loop stability. The constraints are formulated as a set of linear inequalities in the frequency domain. This leads to a convex problem that is scalable with respect to the length of the data and the complexity of the controller. An extension of virtual reference feedback tuning to include disturbance dynamics is also discussed. The proposed data-driven control design is illustrated by a soft gripper impedance control example.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"86 ","pages":"Article 101300"},"PeriodicalIF":2.6,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145645602","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}
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