Pub Date : 2025-01-08DOI: 10.1109/TCNS.2025.3527254
Liping Chen;Chuang Liu;António M. Lopes;Zhiqiang Zhang;YangQuan Chen
This article proposes nonfragile leader–follower consensus control for variable fractional-order multiagent systems under disturbance generated by an exogenous system. The developed technique is directly applicable to fixed fractional-order and integer-order multiagent systems. First, a nonfragile variable fractional-order disturbance observer is introduced, which is able to tolerate a certain degree of parameter uncertainty. Second, by employing the disturbance observer, a novel robust nonfragile consensus control scheme is developed, which not only ensures asymptotic stability of the consensus error system, but also accommodates parameter uncertainty in the physical controller's implementation. Third, new suffi cient conditions for the desired consensus protocol are derived using linear matrix inequalities (LMIs), as well as graph and Lyapunov theory. Finally, simulation examples are presented to illustrate the validity of the theoretical results. The proposed order-dependent LMI condition is less conservative than existing order-independent alternatives.
{"title":"Nonfragile Consensus Strategy for Variable Fractional-Order Multiagent Systems Based on Disturbance Observer","authors":"Liping Chen;Chuang Liu;António M. Lopes;Zhiqiang Zhang;YangQuan Chen","doi":"10.1109/TCNS.2025.3527254","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3527254","url":null,"abstract":"This article proposes nonfragile leader–follower consensus control for variable fractional-order multiagent systems under disturbance generated by an exogenous system. The developed technique is directly applicable to fixed fractional-order and integer-order multiagent systems. First, a nonfragile variable fractional-order disturbance observer is introduced, which is able to tolerate a certain degree of parameter uncertainty. Second, by employing the disturbance observer, a novel robust nonfragile consensus control scheme is developed, which not only ensures asymptotic stability of the consensus error system, but also accommodates parameter uncertainty in the physical controller's implementation. Third, new suffi cient conditions for the desired consensus protocol are derived using linear matrix inequalities (LMIs), as well as graph and Lyapunov theory. Finally, simulation examples are presented to illustrate the validity of the theoretical results. The proposed order-dependent LMI condition is less conservative than existing order-independent alternatives.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1709-1720"},"PeriodicalIF":4.0,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331540","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}
In this article, a unified influence network model incorporating differential privacy mechanisms (DPMs), called the differentially private opinion dynamics (DPODs) model, is proposed. In this model, each individual uses protected opinions rather than the private opinions of his/her neighbors to update his/her private opinions, where the protected opinion of an individual is a blend of private opinions and random noise following Laplace distribution. Building on stochastic analysis techniques and matrix theory, we show that the influence network under consideration converges under specific conditions governing individual sensitivities and interaction weights. In addition, the statistical properties related to convergence accuracy are established by utilizing the Markov inequality to estimate a lower bound on the probability of all individuals' final opinions converging to a neighborhood formed by their initial opinions' convex hull. We further conduct a differential privacy analysis to validate the efficacy of the proposed DPMs in safeguarding the private opinions of all individuals. Finally, two examples, including one of the Karate-Club networks, are provided to shed new light on the effectiveness of the theoretical results.
{"title":"Differentially Private Opinion Dynamics of Influence Networks","authors":"Guanglei Wu;Wenbing Zhang;Shuai Mao;Xiaotai Wu;Yang Tang","doi":"10.1109/TCNS.2025.3526720","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526720","url":null,"abstract":"In this article, a unified influence network model incorporating differential privacy mechanisms (DPMs), called the differentially private opinion dynamics (DPODs) model, is proposed. In this model, each individual uses protected opinions rather than the private opinions of his/her neighbors to update his/her private opinions, where the protected opinion of an individual is a blend of private opinions and random noise following Laplace distribution. Building on stochastic analysis techniques and matrix theory, we show that the influence network under consideration converges under specific conditions governing individual sensitivities and interaction weights. In addition, the statistical properties related to convergence accuracy are established by utilizing the Markov inequality to estimate a lower bound on the probability of all individuals' final opinions converging to a neighborhood formed by their initial opinions' convex hull. We further conduct a differential privacy analysis to validate the efficacy of the proposed DPMs in safeguarding the private opinions of all individuals. Finally, two examples, including one of the Karate-Club networks, are provided to shed new light on the effectiveness of the theoretical results.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1662-1673"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331756","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 : 2025-01-07DOI: 10.1109/TCNS.2025.3526716
Xinhe Wang;Guanghui Wen;Dan Zhao;Tingwen Huang
External disturbances and denial-of-service (DoS) attacks pose significant challenges to the quantized control of multiagent systems (MASs). Most of the existing quantized control strategies primarily focus on designing scaling factors and constructing auxiliary systems without considering external disturbances. Note that these strategies require a highly accurate system model and will lead to the saturation of the quantizer if there exist external disturbances. To overcome the aforementioned shortcomings, a new scaling function is developed in this article by incorporating robustness factors into the scaling function design, significantly enhancing the robustness of the quantization mechanism. Based on this, a robust quantized control strategy is designed to achieve the bounded consensus of linear MASs in the presence of disturbance and DoS attacks, where the tradeoff among quantization level, consensus performance, and resilience to DoS attacks is explored. Besides, the robust design framework shows significant flexibility and efficiency in addressing the resilient control of nonlinear MASs subject to DoS attacks. Numerical simulations are provided to validate the theoretical results.
{"title":"Robust Quantized Consensus of Multiagent Systems Under Disturbance and DoS Attacks","authors":"Xinhe Wang;Guanghui Wen;Dan Zhao;Tingwen Huang","doi":"10.1109/TCNS.2025.3526716","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526716","url":null,"abstract":"External disturbances and denial-of-service (DoS) attacks pose significant challenges to the quantized control of multiagent systems (MASs). Most of the existing quantized control strategies primarily focus on designing scaling factors and constructing auxiliary systems without considering external disturbances. Note that these strategies require a highly accurate system model and will lead to the saturation of the quantizer if there exist external disturbances. To overcome the aforementioned shortcomings, a new scaling function is developed in this article by incorporating robustness factors into the scaling function design, significantly enhancing the robustness of the quantization mechanism. Based on this, a robust quantized control strategy is designed to achieve the bounded consensus of linear MASs in the presence of disturbance and DoS attacks, where the tradeoff among quantization level, consensus performance, and resilience to DoS attacks is explored. Besides, the robust design framework shows significant flexibility and efficiency in addressing the resilient control of nonlinear MASs subject to DoS attacks. Numerical simulations are provided to validate the theoretical results.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1626-1637"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331748","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 : 2025-01-07DOI: 10.1109/TCNS.2025.3526709
Alexander Engelmann;Sungho Shin;François Pacaud;Victor M. Zavala
The operation of large-scale infrastructure networks requires scalable optimization schemes. To guarantee safe system operation, a high degree of feasibility in a small number of iterations is important. Decomposition schemes can help to achieve scalability. In terms of feasibility, however, classical approaches, such as the alternating direction method of multipliers (ADMMs), often converge slowly. In this work, we present primal decomposition schemes for hierarchically structured strongly convex quadratic programs. These schemes offer high degrees of feasibility in a small number of iterations in combination with global convergence guarantees. We benchmark their performance against the centralized off-the-shelf interior-point solver Ipopt and ADMM on problems with up to 300 000 decision variables and constraints. We find that the proposed approaches solve problems as fast as Ipopt, but with reduced communication and without requiring a full model exchange. Moreover, the proposed schemes achieve a higher accuracy than ADMM.
{"title":"Scalable Primal Decomposition Schemes for Large-Scale Infrastructure Networks","authors":"Alexander Engelmann;Sungho Shin;François Pacaud;Victor M. Zavala","doi":"10.1109/TCNS.2025.3526709","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526709","url":null,"abstract":"The operation of large-scale infrastructure networks requires scalable optimization schemes. To guarantee safe system operation, a high degree of feasibility in a small number of iterations is important. Decomposition schemes can help to achieve scalability. In terms of feasibility, however, classical approaches, such as the alternating direction method of multipliers (ADMMs), often converge slowly. In this work, we present primal decomposition schemes for hierarchically structured strongly convex quadratic programs. These schemes offer high degrees of feasibility in a small number of iterations in combination with global convergence guarantees. We benchmark their performance against the centralized off-the-shelf interior-point solver Ipopt and ADMM on problems with up to 300 000 decision variables and constraints. We find that the proposed approaches solve problems as fast as Ipopt, but with reduced communication and without requiring a full model exchange. Moreover, the proposed schemes achieve a higher accuracy than ADMM.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1687-1698"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331754","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 : 2025-01-07DOI: 10.1109/TCNS.2025.3526705
Jonas Hansson;Emma Tegling
This article presents a novel control design for vehicular formations as an alternative to alignment through conventional consensus protocols for second-order systems. The design is motivated by the closed-loop system, which we construct as first-order systems connected in series, and is therefore called serial consensus. The serial consensus design will guarantee the stability of the closed-loop system under the minimum requirement of the underlying communication graph containing a directed spanning tree, which is not generally true for conventional consensus. As our main result, we show that the serial consensus design gives bounds on the worst-case transient behavior of the formation, which is independent of the number of vehicles and the underlying graph structure. In particular, this shows that the serial consensus design guarantees the string stability of the formation and is, therefore, suitable for directed formations and communication topologies. We show that serial consensus can be implemented through message passing or measurements to neighbors at most two hops away. We illustrate our results through numerical examples.
{"title":"Closed-Loop Design for Scalable Performance of Vehicular Formations","authors":"Jonas Hansson;Emma Tegling","doi":"10.1109/TCNS.2025.3526705","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526705","url":null,"abstract":"This article presents a novel control design for vehicular formations as an alternative to alignment through conventional consensus protocols for second-order systems. The design is motivated by the closed-loop system, which we construct as first-order systems connected in series, and is therefore called <italic>serial consensus.</i> The serial consensus design will guarantee the stability of the closed-loop system under the minimum requirement of the underlying communication graph containing a directed spanning tree, which is not generally true for conventional consensus. As our main result, we show that the serial consensus design gives bounds on the worst-case transient behavior of the formation, which is independent of the number of vehicles and the underlying graph structure. In particular, this shows that the serial consensus design guarantees the string stability of the formation and is, therefore, suitable for directed formations and communication topologies. We show that serial consensus can be implemented through message passing or measurements to neighbors at most two hops away. We illustrate our results through numerical examples.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1577-1586"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331708","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 : 2025-01-07DOI: 10.1109/TCNS.2025.3526555
Yantao Li;Chen Chen;Keke Zhang;Dong Li;Qingguo Lü;Shaojiang Deng;Huaqing Li
This article investigates distributed online optimization for a group of agents communicating on undirected networks. The objective is to collaboratively minimize the sum of locally known convex cost functions while overcoming communication bandwidth limitations. To tackle this challenge, we propose the Q-DADAM algorithm, a quantized distributed adaptive momentum method that ensures that agents interact with neighbors to optimize the global cost function collectively. Unlike many existing distributed online optimization algorithms that overlook communication bandwidth constraints, the Q-DADAM algorithm involves random quantization to effectively reduce the data transmission volume, making it more practical for applications with limited channel capacity. Different from existing algorithms that neglect adaptive momentum methods, the Q-DADAM algorithm incorporates these adaptive momentum methods, contributing to improved convergence and superior performance. Theoretical analysis demonstrates that the Q-DADAM algorithm with appropriate step size and quantization level can reduce communication traffic and achieve sublinear dynamic regret. Simulation experiments validate the practicality and effectiveness of the Q-DADAM algorithm. In addition, we discuss the impacts on the convergence of the Q-DADAM algorithm under different quantization levels and the number of agents.
{"title":"Q-DADAM: A Quantized Distributed Online Optimization Algorithm With Adaptive Momentum","authors":"Yantao Li;Chen Chen;Keke Zhang;Dong Li;Qingguo Lü;Shaojiang Deng;Huaqing Li","doi":"10.1109/TCNS.2025.3526555","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526555","url":null,"abstract":"This article investigates distributed online optimization for a group of agents communicating on undirected networks. The objective is to collaboratively minimize the sum of locally known convex cost functions while overcoming communication bandwidth limitations. To tackle this challenge, we propose the Q-DADAM algorithm, a quantized distributed adaptive momentum method that ensures that agents interact with neighbors to optimize the global cost function collectively. Unlike many existing distributed online optimization algorithms that overlook communication bandwidth constraints, the Q-DADAM algorithm involves random quantization to effectively reduce the data transmission volume, making it more practical for applications with limited channel capacity. Different from existing algorithms that neglect adaptive momentum methods, the Q-DADAM algorithm incorporates these adaptive momentum methods, contributing to improved convergence and superior performance. Theoretical analysis demonstrates that the Q-DADAM algorithm with appropriate step size and quantization level can reduce communication traffic and achieve sublinear dynamic regret. Simulation experiments validate the practicality and effectiveness of the Q-DADAM algorithm. In addition, we discuss the impacts on the convergence of the Q-DADAM algorithm under different quantization levels and the number of agents.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1540-1551"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331750","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 : 2025-01-07DOI: 10.1109/TCNS.2025.3526704
Cong Bi;Xiang Xu;Lu Liu;Gang Feng
This article considers the leader-following consensus problem of multiagent systems subject to unbounded distributed communication delays under the condition that only the neighboring agents of the leader have access to the information on both the system matrix and the state of the leader. A novel adaptive distributed observer is proposed to estimate both the system matrix and the state of the leader under unbounded distributed communication delays, without requiring that the information of the unbounded delays is known a priori. A key technical result is first established, and a novel distributed controller is then developed based on the proposed distributed observer. It is shown that the resulting closed-loop system achieves the desired consensus. Finally, the effectiveness of the theoretical results is validated by two simulation examples.
{"title":"Consensus of Multiagent Systems Under Unbounded Communication Delays via Adaptive Distributed Observers","authors":"Cong Bi;Xiang Xu;Lu Liu;Gang Feng","doi":"10.1109/TCNS.2025.3526704","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526704","url":null,"abstract":"This article considers the leader-following consensus problem of multiagent systems subject to unbounded distributed communication delays under the condition that only the neighboring agents of the leader have access to the information on both the system matrix and the state of the leader. A novel <italic>adaptive</i> distributed observer is proposed to estimate both the system matrix and the state of the leader under unbounded distributed communication delays, without requiring that the information of the unbounded delays is known a priori. A key technical result is first established, and a novel distributed controller is then developed based on the proposed distributed observer. It is shown that the resulting closed-loop system achieves the desired consensus. Finally, the effectiveness of the theoretical results is validated by two simulation examples.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1613-1625"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331572","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 : 2025-01-07DOI: 10.1109/TCNS.2025.3526678
MirSaleh Bahavarnia;Junyi Ji;Ahmad F. Taha;Daniel B. Work
The main objective of the connected and automated vehicle (CAV) platoon control problem is to regulate CAVs' position while ensuring stability and accounting for vehicle dynamics. Although this problem has been studied in the literature, existing research has some limitations. This article presents two new theoretical results that address these limitations: the synthesis of unrealistic high-gain control parameters due to the lack of a systematic way to incorporate the lower and upper bounds on the control parameters, and the performance sensitivity to the communication delay due to inaccurate Taylor series approximation. To be more precise, taking advantage of the well-known Padé approximation, this article proposes a constrained CAV platoon controller synthesis that systematically incorporates the lower and upper bounds on the control parameters, and significantly improves the performance sensitivity to the communication delay. The effectiveness of the presented results is verified through conducting extensive numerical simulations. The proposed controller effectively attenuates the stop-and-go disturbance—a single cycle of deceleration followed by acceleration—amplification throughout the mixed platoon (consisting of CAVs and human-driven vehicles). Modern transportation systems will benefit from the proposed CAV controls in terms of effective disturbance attenuation as it will potentially reduce collisions.
{"title":"On the Constrained CAV Platoon Control Problem","authors":"MirSaleh Bahavarnia;Junyi Ji;Ahmad F. Taha;Daniel B. Work","doi":"10.1109/TCNS.2025.3526678","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526678","url":null,"abstract":"The main objective of the connected and automated vehicle (CAV) platoon control problem is to regulate CAVs' position while ensuring stability and accounting for vehicle dynamics. Although this problem has been studied in the literature, existing research has some limitations. This article presents two new theoretical results that address these limitations: the synthesis of unrealistic high-gain control parameters due to the lack of a systematic way to incorporate the lower and upper bounds on the control parameters, and the performance sensitivity to the communication delay due to inaccurate Taylor series approximation. To be more precise, taking advantage of the well-known Padé approximation, this article proposes a constrained CAV platoon controller synthesis that systematically incorporates the lower and upper bounds on the control parameters, and significantly improves the performance sensitivity to the communication delay. The effectiveness of the presented results is verified through conducting extensive numerical simulations. The proposed controller effectively attenuates the <italic>stop-and-go disturbance</i>—a single cycle of deceleration followed by acceleration—amplification throughout the mixed platoon (consisting of CAVs and human-driven vehicles). Modern transportation systems will benefit from the proposed CAV controls in terms of effective disturbance attenuation as it will potentially reduce collisions.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1552-1564"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10829967","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-07DOI: 10.1109/TCNS.2025.3526723
Simeng Guo;Wenling Li;Yang Liu;Jia Song
In this article, a privacy-preserving distributed extended Kalman filter based on average consensus information fusion is designed for graphical nonlinear systems. The privacy-preserving approach adopted is realized based on a combination of state decomposition and noise injection methods. On the one hand, the Laplacian matrix of the graphical nonlinear system is utilized to design a distributed filter in the graph frequency domain, featuring a diagonal gain matrix that significantly enhances filtering performance; on the other hand, a recursive least squares filter is applied at the sensor nodes to filter out the privacy-preserving noise, thus making the eavesdropper's observation mismatch with the iterative update of the sensor state, which effectively improves the filtering and privacy performance. Subsequently, the boundedness of the filtering error is shown, and the privacy performance against eavesdroppers is discussed. Finally, a simulation example of a power system demonstrates the superiority of our proposed algorithm.
{"title":"Privacy-Preserving Distributed Extended Kalman Filtering for Graphical Nonlinear Systems","authors":"Simeng Guo;Wenling Li;Yang Liu;Jia Song","doi":"10.1109/TCNS.2025.3526723","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526723","url":null,"abstract":"In this article, a privacy-preserving distributed extended Kalman filter based on average consensus information fusion is designed for graphical nonlinear systems. The privacy-preserving approach adopted is realized based on a combination of state decomposition and noise injection methods. On the one hand, the Laplacian matrix of the graphical nonlinear system is utilized to design a distributed filter in the graph frequency domain, featuring a diagonal gain matrix that significantly enhances filtering performance; on the other hand, a recursive least squares filter is applied at the sensor nodes to filter out the privacy-preserving noise, thus making the eavesdropper's observation mismatch with the iterative update of the sensor state, which effectively improves the filtering and privacy performance. Subsequently, the boundedness of the filtering error is shown, and the privacy performance against eavesdroppers is discussed. Finally, a simulation example of a power system demonstrates the superiority of our proposed algorithm.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1674-1686"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331541","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 : 2025-01-07DOI: 10.1109/TCNS.2025.3526715
Alexander Engelmann;Maísa Beraldo Bandeira;Timm Faulwasser
Safe and economic operation of networked systems is challenging. Optimization-based schemes are frequently considered, since they achieve near-optimality while ensuring safety via the explicit consideration of constraints. In applications, these schemes often require solving large-scale optimization problems. Iterative techniques from distributed optimization are frequently proposed for complexity reduction. Yet, they achieve feasibility only asymptotically, which induces a substantial computational burden. This work presents an approximate dynamic programming scheme for tree-structured optimization problems, which is guaranteed to deliver a feasible solution in “one shot,” i.e., in one backward-forward iteration over all subproblems. Our approach generalizes methods from seemingly disconnected domains, such as power systems and optimal control. We demonstrate its efficacy for problems with nonconvex constraints via numerical examples from both domains.
{"title":"Approximate Dynamic Programming With Feasibility Guarantees","authors":"Alexander Engelmann;Maísa Beraldo Bandeira;Timm Faulwasser","doi":"10.1109/TCNS.2025.3526715","DOIUrl":"https://doi.org/10.1109/TCNS.2025.3526715","url":null,"abstract":"Safe and economic operation of networked systems is challenging. Optimization-based schemes are frequently considered, since they achieve near-optimality while ensuring safety via the explicit consideration of constraints. In applications, these schemes often require solving large-scale optimization problems. Iterative techniques from distributed optimization are frequently proposed for complexity reduction. Yet, they achieve feasibility only asymptotically, which induces a substantial computational burden. This work presents an approximate dynamic programming scheme for tree-structured optimization problems, which is guaranteed to deliver a feasible solution in “one shot,” i.e., in one backward-forward iteration over all subproblems. Our approach generalizes methods from seemingly disconnected domains, such as power systems and optimal control. We demonstrate its efficacy for problems with nonconvex constraints via numerical examples from both domains.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"12 2","pages":"1565-1576"},"PeriodicalIF":4.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144331749","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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