Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded...Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.展开更多
Steam power systems(SPSs)in industrial parks are the typical utility systems for heat and electricity supply.In SPSs,electricity is generated by steam turbines,and steam is generally produced and supplied at multiple ...Steam power systems(SPSs)in industrial parks are the typical utility systems for heat and electricity supply.In SPSs,electricity is generated by steam turbines,and steam is generally produced and supplied at multiple levels to serve the heat demands of consumers with different temperature grades,so that energy is utilized in cascade.While a large number of steam levels enhances energy utilization efficiency,it also tends to cause a complex steam pipeline network in the industrial park.In practice,a moderate number of steam levels is always adopted in SPSs,leading to temperature mismatches between heat supply and demand for some consumers.This study proposes a distributed steam turbine system(DSTS)consisting of main steam turbines on the energy supply side and auxiliary steam turbines on the energy consumption side,aiming to balance the heat production costs,the distance-related costs,and the electricity generation of SPSs in industrial parks.A mixed-integer nonlinear programming model is established for the optimization of SPSs,with the objective of minimizing the total annual cost(TAC).The optimal number of steam levels and the optimal configuration of DSTS for an industrial park can be determined by solving the model.A case study demonstrates that the TAC of the SPS is reduced by 220.6×10^(3)USD(2.21%)through the arrangement of auxiliary steam turbines.The sub-optimal number of steam levels and a non-optimal operating condition slightly increase the TAC by 0.46%and 0.28%,respectively.The sensitivity analysis indicates that the optimal number of steam levels tends to decrease from 3 to 2 as electricity price declines.展开更多
This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise co...This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise controllers for each agent, enabling them to precisely track the average of multiple time-varying reference signals. By averaging these signals, we can mitigate the influence of errors and uncertainties arising dur-ing measurements, thereby enhancing the robustness and stabi-lity of the system. A distributed fixed-time average estimator is proposed to estimate the average value of global reference sig-nals utilizing local information and communication with neigh-bors. Subsequently, a fixed-time sliding mode controller is intro-duced incorporating a state-dependent sliding mode function coupled with a variable exponent coefficient to achieve dis-tributed average tracking of reference signals, and rigorous ana-lytical methods are employed to substantiate the fixed-time sta-bility. Finally, numerical simulation results are provided to vali-date the effectiveness of the proposed methodology, offering insights into its practical application and robust performance.展开更多
The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addre...The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addressing these core bottlenecks.This paper provides a systematic review of the research background,technological evolution,core systems,key challenges,and future directions of AI technology in the field of distributed photovoltaic power generation system optimization.At the same time,this paper analyzes the current technical bottlenecks and cutting-edge response strategies.Finally,it explores fusion innovation directions such as quantum-classical hybrid algorithms and neural symbolic systems,as well as business model expansion paths such as carbon finance integration and community energy autonomy.展开更多
Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the p...Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the production line,the manufacturing layer and the workshop layer.The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations(PDEs)based on the law of mass conservation.展开更多
Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under dir...Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.展开更多
In this paper, distributed event-triggered performance constraint control is proposed for Heterogeneous Multiagent Systems (HMASs) including quadrotor unmanned aerial vehicles and unmanned ground vehicles in the prese...In this paper, distributed event-triggered performance constraint control is proposed for Heterogeneous Multiagent Systems (HMASs) including quadrotor unmanned aerial vehicles and unmanned ground vehicles in the presence of unknown external disturbances. To tackle the problem of different dynamic characteristics and facilitate the controller design, the virtual variable is introduced in the z axis of the nonlinear model of unmanned ground vehicles. By using this approach, a universal model is established for the HMAS. Moreover, a distributed disturbance observer is established to cope with the adverse influence of the external disturbances. Then, an Appointed-Time Prescribed Performance Function (ATPPF) is designed to restrict the tracking error in the predefined regions. On this basis, the distributed performance constraint controller is proposed for the HMAS based on the ATPPF and the distributed disturbance observer. Furthermore, the improved event-triggered mechanism is proposed with a dynamic threshold, which depends on the distance between the tracking error and the boundary of the ATPPF. Finally, the effectiveness of the proposed control method is verified by the comparative experiments on an HMAS.展开更多
This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity fa...This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.展开更多
Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multip...Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multiple-Output(MIMO)Orthogonal Frequency Division Multiplexing(OFDM)signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals.First,we analyze the Cramer-Rao Lower Bound(CRLB)of parameter estimation.Then,the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance.Finally,we propose a more accurate estimation method that uses Canonical Polyadic Decomposition(CPD)of the third-order tensor to obtain the parameter matrices.Due to the characteristic of the column structure of the parameter matrices,we only need to use DFT/IDFT to recover the parameters of multiple targets.The simulation results show that tensor-based estimation method can achieve a performance close to CRLB,and the estimation performance can be improved by optimizing the transmit powers.展开更多
As urban areas expand and water demand intensifies,the need for efficient and reliable water distribution systems becomes increasingly critical.A widely used infrastructure management approach involves partitioning wa...As urban areas expand and water demand intensifies,the need for efficient and reliable water distribution systems becomes increasingly critical.A widely used infrastructure management approach involves partitioning water distribution networks(WDNs)into district metered areas(DMAs).However,suboptimal designs of DMA partitioning can lead to inefficiencies and increased costs.This study presents a core-peripheryinformed approach for DMA design that explicitly utilises the natural division between a densely connected core and a sparsely connected periphery.Incorporating this structural framework enhances network resilience,improves water pressure stability,and optimises boundary device placement.The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas,applies a community structure detection algorithm conditioned by these areas,and uses an optimisation model to determine the optimal placement of boundary devices,enhancing network resilience and reducing costs.When applied to the Modena WDN in Italy,this approach demonstrates improved pressure stability and significant cost reductions compared to traditional methods.Overall,the findings highlight the practical benefits of the core-periphery-based DMA design,offering a scalable and data-driven solution for urban water distribution systems.展开更多
Within the context of ground-air cooperation,the distributed formation trajectory tracking control problems for the Heterogeneous Multi-Agent Systems(HMASs)is studied.First,considering external disturbances and model ...Within the context of ground-air cooperation,the distributed formation trajectory tracking control problems for the Heterogeneous Multi-Agent Systems(HMASs)is studied.First,considering external disturbances and model uncertainties,a graph theory-based formation control protocol is designed for the HMASs consisting of Unmanned Aerial Vehicles(UAVs)and Unmanned Ground Vehicles(UGVs).Subsequently,a formation trajectory tracking control strategy employing adaptive Fractional-Order Sliding Mode Control(FOSMC)method is developed,and a Feedback Multilayer Fuzzy Neural Network(FMFNN)is introduced to estimate the lumped uncertainties.This approach empowers HMASs to adaptively follow the expected trajectory and adopt the designated formation configuration,even in the presence of various uncertainties.Additionally,an event-triggered mechanism is incorporated into the controller to reduce the update frequency of the controller and minimize the communication exchange among the agents,and the absence of Zeno behavior is rigorously demonstrated by an integral inequality analysis.Finally,to confirm the effectiveness of the proposed formation control protocol,some numerical simulations are presented.展开更多
The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in...The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a varietyof industries, including access control, law enforcement, surveillance, and internet communication. However,the growing usage of face recognition technology has created serious concerns about data monitoring and userprivacy preferences, especially in context-aware systems. In response to these problems, this study provides a novelframework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain,and distributed computing to solve privacy concerns while maintaining exact face recognition. The framework’spainstaking design and execution strive to strike a compromise between precise face recognition and protectingpersonal data integrity in an increasingly interconnected environment. Using cutting-edge tools like Dlib for faceanalysis,Ray Cluster for distributed computing, and Blockchain for decentralized identity verification, the proposedsystem provides scalable and secure facial analysis while protecting user privacy. The study’s contributions includethe creation of a sustainable and scalable solution for privacy-aware face recognition, the implementation of flexibleprivacy computing approaches based on Blockchain networks, and the demonstration of higher performanceover previous methods. Specifically, the proposed StyleGAN model has an outstanding accuracy rate of 93.84%while processing high-resolution images from the CelebA-HQ dataset, beating other evaluated models such asProgressive GAN 90.27%, CycleGAN 89.80%, and MGAN 80.80%. With improvements in accuracy, speed, andprivacy protection, the framework has great promise for practical use in a variety of fields that need face recognitiontechnology. This study paves the way for future research in privacy-enhanced face recognition systems, emphasizingthe significance of using cutting-edge technology to meet rising privacy issues in digital identity.展开更多
We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that prov...We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.展开更多
Distributed matrix-scaled consensus is a kind of generalized cooperative control problem and has broad applications in the field of social network and engineering.This paper addresses the robust distributed matrix-sca...Distributed matrix-scaled consensus is a kind of generalized cooperative control problem and has broad applications in the field of social network and engineering.This paper addresses the robust distributed matrix-scaled consensus of perturbed multi-agent systems suffering from unknown disturbances.Distributed discontinuous protocols are first proposed to drive agents to achieve cluster consensus and suppress the effect of disturbances.Adaptive protocols with time-varying gains obeying differential equations are also designed,which are completely distributed and rely on no global information.Using the boundary layer technique,smooth protocols are proposed to avoid the unexpected chattering effect due to discontinuous functions.As a cost,under the designed smooth protocols,the defined matrix-scaled consensus error tends to a residual set rather than zero,in which the residual bound is arbitrary small by choosing proper parameters.Moreover,distributed dynamic event-based matrix-scalar consensus controllers are also proposed to avoid continuous communications.Simulation examples are provided to further verify the designed algorithms.展开更多
This paper aims to study the leader-following consensus of linear multi-agent systems on undirected graphs.Specifically,we construct an adaptive event-based protocol that can be implemented in a fully distributed way ...This paper aims to study the leader-following consensus of linear multi-agent systems on undirected graphs.Specifically,we construct an adaptive event-based protocol that can be implemented in a fully distributed way by using only local relative information.This protocol is also resource-friendly as it will be updated only when the agent violates the designed event-triggering function.A sufficient condition is proposed for the leader-following consensus of linear multi-agent systems based on the Lyapunov approach,and the Zeno-behavior is excluded.Finally,two numerical examples are provided to illustrate the effectiveness of the theoretical results.展开更多
Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost prob...Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost problems of both hardware and power consumption.In this paper,we investigate multiple reconfigurable intelligent surfaces(RISs)aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way.To overcome the centralized high complexity and avoid frequent information exchanges,a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance.In particular,the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points,and phase shifts are obtained centrally based on the Riemannian conjugate gradient(RCG)manifold method.Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.展开更多
A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion mo...A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion model （BEM） of the channel, the joint-sparsity of MIMO-OFDM channels is described. The sparse characteristics enable us to cast the channel estimation as a distributed compressed sensing （DCS） problem. Then, a low complexity DCS-based estimation scheme is designed. Compared with the conventional compressed channel estimators based on the compressed sensing （CS） theory, the DCS-based method has an improved efficiency because it reconstructs the MIMO channels jointly rather than addresses them separately. Furthermore, the group-sparse structure of each single channel is also depicted. To effectively use this additional structure of the sparsity pattern, the DCS algorithm is modified. The modified algorithm can further enhance the estimation performance. Simulation results demonstrate the superiority of our method over fast fading channels in MIMO-OFDM systems.展开更多
Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers ...Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.展开更多
The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications direct...The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.展开更多
This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. ...This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search algorithms.Moreover, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.展开更多
基金supported by the National Natural Science Foundation of China(62303273,62373226)the National Research Foundation,Singapore through the Medium Sized Center for Advanced Robotics Technology Innovation(WP2.7)
文摘Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.
基金Financial support from the National Natural Science Foundation of China under Grant(22393954 and 22078358)is gratefully acknowledged.
文摘Steam power systems(SPSs)in industrial parks are the typical utility systems for heat and electricity supply.In SPSs,electricity is generated by steam turbines,and steam is generally produced and supplied at multiple levels to serve the heat demands of consumers with different temperature grades,so that energy is utilized in cascade.While a large number of steam levels enhances energy utilization efficiency,it also tends to cause a complex steam pipeline network in the industrial park.In practice,a moderate number of steam levels is always adopted in SPSs,leading to temperature mismatches between heat supply and demand for some consumers.This study proposes a distributed steam turbine system(DSTS)consisting of main steam turbines on the energy supply side and auxiliary steam turbines on the energy consumption side,aiming to balance the heat production costs,the distance-related costs,and the electricity generation of SPSs in industrial parks.A mixed-integer nonlinear programming model is established for the optimization of SPSs,with the objective of minimizing the total annual cost(TAC).The optimal number of steam levels and the optimal configuration of DSTS for an industrial park can be determined by solving the model.A case study demonstrates that the TAC of the SPS is reduced by 220.6×10^(3)USD(2.21%)through the arrangement of auxiliary steam turbines.The sub-optimal number of steam levels and a non-optimal operating condition slightly increase the TAC by 0.46%and 0.28%,respectively.The sensitivity analysis indicates that the optimal number of steam levels tends to decrease from 3 to 2 as electricity price declines.
基金supported by the National Natural Science Foundation of China(61673130).
文摘This paper investigates the sliding-mode-based fixed-time distributed average tracking (DAT) problem for multiple Euler-Lagrange systems in the presence of external distur-bances. The primary objective is to devise controllers for each agent, enabling them to precisely track the average of multiple time-varying reference signals. By averaging these signals, we can mitigate the influence of errors and uncertainties arising dur-ing measurements, thereby enhancing the robustness and stabi-lity of the system. A distributed fixed-time average estimator is proposed to estimate the average value of global reference sig-nals utilizing local information and communication with neigh-bors. Subsequently, a fixed-time sliding mode controller is intro-duced incorporating a state-dependent sliding mode function coupled with a variable exponent coefficient to achieve dis-tributed average tracking of reference signals, and rigorous ana-lytical methods are employed to substantiate the fixed-time sta-bility. Finally, numerical simulation results are provided to vali-date the effectiveness of the proposed methodology, offering insights into its practical application and robust performance.
文摘The rapid development of artificial intelligence(AI)technology,particularly breakthroughs in branches such as deep learning,reinforcement learning,and federated learning,has provided powerful technical tools for addressing these core bottlenecks.This paper provides a systematic review of the research background,technological evolution,core systems,key challenges,and future directions of AI technology in the field of distributed photovoltaic power generation system optimization.At the same time,this paper analyzes the current technical bottlenecks and cutting-edge response strategies.Finally,it explores fusion innovation directions such as quantum-classical hybrid algorithms and neural symbolic systems,as well as business model expansion paths such as carbon finance integration and community energy autonomy.
文摘Dear Editor,This letter focuses on the distributed cooperative regulation problem for a class of networked re-entrant manufacturing systems(RMSs).The networked system is structured with a three-tier architecture:the production line,the manufacturing layer and the workshop layer.The dynamics of re-entrant production lines are governed by hyperbolic partial differential equations(PDEs)based on the law of mass conservation.
基金supported by the National Natural Science Foundation of China(62073113,62003122,62303148)the Fundamental Research Funds for the Central Universities(MCCSE2023A01,JZ2023HGTA0201,JZ2023HGQA0109)the Anhui Provincial Natural Science Foundation(2308085QF204)
文摘Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.
基金supported in part by the National Natural Science Foundation of China(Nos.U23B2036,U2013201).
文摘In this paper, distributed event-triggered performance constraint control is proposed for Heterogeneous Multiagent Systems (HMASs) including quadrotor unmanned aerial vehicles and unmanned ground vehicles in the presence of unknown external disturbances. To tackle the problem of different dynamic characteristics and facilitate the controller design, the virtual variable is introduced in the z axis of the nonlinear model of unmanned ground vehicles. By using this approach, a universal model is established for the HMAS. Moreover, a distributed disturbance observer is established to cope with the adverse influence of the external disturbances. Then, an Appointed-Time Prescribed Performance Function (ATPPF) is designed to restrict the tracking error in the predefined regions. On this basis, the distributed performance constraint controller is proposed for the HMAS based on the ATPPF and the distributed disturbance observer. Furthermore, the improved event-triggered mechanism is proposed with a dynamic threshold, which depends on the distance between the tracking error and the boundary of the ATPPF. Finally, the effectiveness of the proposed control method is verified by the comparative experiments on an HMAS.
文摘This paper introduces an optimized planning approach for integrating photovoltaic as distributed generation (PV-DG) into the radial distribution power systems, utilizing exhaustive load flow (ELF), loss sensitivity factor (LSF), genetic algorithms (GA) methods, and numerical method based on LSF. The methodology aims to determine the optimal allocation and sizing of multiple PV-DG to minimize power loss through time series power flow analysis. An approach utilizing continuous sensitivity analysis is developed and inherently leverages power flow and loss equations to compute LSF of all buses in the system towards employing a dynamic PV-DG model for more accurate results. The algorithm uses a numerical grid search method to optimize PV-DG placement in a power distribution system, focusing on minimizing system losses. It combines iterative analysis, sensitivity assessment, and comprehensive visualization to identify and present the optimal PV-DG configurations. The present-ed algorithms are verified through co-simulation framework combining MATLAB and OpenDSS to carry out analysis for 12-bus radial distribution test system. The proposed numerical method is compared with other algorithms, such as ELF, LSF methods, and Genetic Algorithms (GA). Results show that the proposed numerical method performs well in comparison with LSF and ELF solutions.
基金supported by the National Natural Science Foundation of China under grants 62072229,U1936201,62071220,61976113joint project of China Mobile Research Institute&X-NET。
文摘Dual-function communication radar systems use common Radio Frequency(RF)signals are used for both communication and detection.For better compatibility with existing communication systems,we adopt Multiple-Input Multiple-Output(MIMO)Orthogonal Frequency Division Multiplexing(OFDM)signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals.First,we analyze the Cramer-Rao Lower Bound(CRLB)of parameter estimation.Then,the transmit powers over different subcarriers are optimized to achieve the best tradeoff between the transmission rate and the estimation performance.Finally,we propose a more accurate estimation method that uses Canonical Polyadic Decomposition(CPD)of the third-order tensor to obtain the parameter matrices.Due to the characteristic of the column structure of the parameter matrices,we only need to use DFT/IDFT to recover the parameters of multiple targets.The simulation results show that tensor-based estimation method can achieve a performance close to CRLB,and the estimation performance can be improved by optimizing the transmit powers.
文摘As urban areas expand and water demand intensifies,the need for efficient and reliable water distribution systems becomes increasingly critical.A widely used infrastructure management approach involves partitioning water distribution networks(WDNs)into district metered areas(DMAs).However,suboptimal designs of DMA partitioning can lead to inefficiencies and increased costs.This study presents a core-peripheryinformed approach for DMA design that explicitly utilises the natural division between a densely connected core and a sparsely connected periphery.Incorporating this structural framework enhances network resilience,improves water pressure stability,and optimises boundary device placement.The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas,applies a community structure detection algorithm conditioned by these areas,and uses an optimisation model to determine the optimal placement of boundary devices,enhancing network resilience and reducing costs.When applied to the Modena WDN in Italy,this approach demonstrates improved pressure stability and significant cost reductions compared to traditional methods.Overall,the findings highlight the practical benefits of the core-periphery-based DMA design,offering a scalable and data-driven solution for urban water distribution systems.
基金supported by the Beijing Municipal Science&Technology Commission China(No.Z19111000270000)the National Natural Science Foundation of China(Nos.62203050,51774042).
文摘Within the context of ground-air cooperation,the distributed formation trajectory tracking control problems for the Heterogeneous Multi-Agent Systems(HMASs)is studied.First,considering external disturbances and model uncertainties,a graph theory-based formation control protocol is designed for the HMASs consisting of Unmanned Aerial Vehicles(UAVs)and Unmanned Ground Vehicles(UGVs).Subsequently,a formation trajectory tracking control strategy employing adaptive Fractional-Order Sliding Mode Control(FOSMC)method is developed,and a Feedback Multilayer Fuzzy Neural Network(FMFNN)is introduced to estimate the lumped uncertainties.This approach empowers HMASs to adaptively follow the expected trajectory and adopt the designated formation configuration,even in the presence of various uncertainties.Additionally,an event-triggered mechanism is incorporated into the controller to reduce the update frequency of the controller and minimize the communication exchange among the agents,and the absence of Zeno behavior is rigorously demonstrated by an integral inequality analysis.Finally,to confirm the effectiveness of the proposed formation control protocol,some numerical simulations are presented.
文摘The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a varietyof industries, including access control, law enforcement, surveillance, and internet communication. However,the growing usage of face recognition technology has created serious concerns about data monitoring and userprivacy preferences, especially in context-aware systems. In response to these problems, this study provides a novelframework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain,and distributed computing to solve privacy concerns while maintaining exact face recognition. The framework’spainstaking design and execution strive to strike a compromise between precise face recognition and protectingpersonal data integrity in an increasingly interconnected environment. Using cutting-edge tools like Dlib for faceanalysis,Ray Cluster for distributed computing, and Blockchain for decentralized identity verification, the proposedsystem provides scalable and secure facial analysis while protecting user privacy. The study’s contributions includethe creation of a sustainable and scalable solution for privacy-aware face recognition, the implementation of flexibleprivacy computing approaches based on Blockchain networks, and the demonstration of higher performanceover previous methods. Specifically, the proposed StyleGAN model has an outstanding accuracy rate of 93.84%while processing high-resolution images from the CelebA-HQ dataset, beating other evaluated models such asProgressive GAN 90.27%, CycleGAN 89.80%, and MGAN 80.80%. With improvements in accuracy, speed, andprivacy protection, the framework has great promise for practical use in a variety of fields that need face recognitiontechnology. This study paves the way for future research in privacy-enhanced face recognition systems, emphasizingthe significance of using cutting-edge technology to meet rising privacy issues in digital identity.
基金Project supported by the National Natural Science Foundation of China (Grant No.62073045)。
文摘We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.
基金supported in part by the National Key Research and Development Program of China(No.2020AAA0108905)by the National Natural Science Foundation of China(Nos.62103302,62273262,62088101)+7 种基金by the Shanghai Sailing Program(No.21YF1450300)by the Shanghai Chenguang Program(No.22CGA19)by the Shanghai Municipal Science and Technology Major Project(No.2021SHZDZX0100)by the Shanghai Science and Technology Planning Project(Nos.21ZR1466400,22QA1408500)by the Shanghai Municipal Commission of Science and Technology Project(No.19511132101)by the Fundamental Research Funds for the Central Universities(No.2022-5-YB-05)by the Industry,Education and Research Innovation Foundation of Chinese University(Nos.2021ZYA02008,2021ZYA03004)by the Special Fund for Independent Innovation of Aero Engine Corporation of China(No.ZZCX-2021-007).
文摘Distributed matrix-scaled consensus is a kind of generalized cooperative control problem and has broad applications in the field of social network and engineering.This paper addresses the robust distributed matrix-scaled consensus of perturbed multi-agent systems suffering from unknown disturbances.Distributed discontinuous protocols are first proposed to drive agents to achieve cluster consensus and suppress the effect of disturbances.Adaptive protocols with time-varying gains obeying differential equations are also designed,which are completely distributed and rely on no global information.Using the boundary layer technique,smooth protocols are proposed to avoid the unexpected chattering effect due to discontinuous functions.As a cost,under the designed smooth protocols,the defined matrix-scaled consensus error tends to a residual set rather than zero,in which the residual bound is arbitrary small by choosing proper parameters.Moreover,distributed dynamic event-based matrix-scalar consensus controllers are also proposed to avoid continuous communications.Simulation examples are provided to further verify the designed algorithms.
基金National Natural Science Foundation of China(Nos.U22B2040 and 62233003)Fundamental Research Funds for the Central Universities(No.lzujbky-2022-kb12)。
文摘This paper aims to study the leader-following consensus of linear multi-agent systems on undirected graphs.Specifically,we construct an adaptive event-based protocol that can be implemented in a fully distributed way by using only local relative information.This protocol is also resource-friendly as it will be updated only when the agent violates the designed event-triggering function.A sufficient condition is proposed for the leader-following consensus of linear multi-agent systems based on the Lyapunov approach,and the Zeno-behavior is excluded.Finally,two numerical examples are provided to illustrate the effectiveness of the theoretical results.
文摘Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost problems of both hardware and power consumption.In this paper,we investigate multiple reconfigurable intelligent surfaces(RISs)aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way.To overcome the centralized high complexity and avoid frequent information exchanges,a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance.In particular,the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points,and phase shifts are obtained centrally based on the Riemannian conjugate gradient(RCG)manifold method.Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.
基金Supported by the National Natural Science Foundation of China(61077022)
文摘A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion model （BEM） of the channel, the joint-sparsity of MIMO-OFDM channels is described. The sparse characteristics enable us to cast the channel estimation as a distributed compressed sensing （DCS） problem. Then, a low complexity DCS-based estimation scheme is designed. Compared with the conventional compressed channel estimators based on the compressed sensing （CS） theory, the DCS-based method has an improved efficiency because it reconstructs the MIMO channels jointly rather than addresses them separately. Furthermore, the group-sparse structure of each single channel is also depicted. To effectively use this additional structure of the sparsity pattern, the DCS algorithm is modified. The modified algorithm can further enhance the estimation performance. Simulation results demonstrate the superiority of our method over fast fading channels in MIMO-OFDM systems.
文摘Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.
文摘The literature on multi-attribute optimization for renewable energy source(RES)placement in deregulated power markets is extensive and diverse in methodology.This study focuses on the most relevant publications directly addressing the research problem at hand.Similarly,while the body of work on optimal location and sizing of renewable energy generators(REGs)in balanced distribution systems is substantial,only the most pertinent sources are cited,aligning closely with the study’s objective function.A comprehensive literature review reveals several key research areas:RES integration,RES-related optimization techniques,strategic placement of wind and solar generation,and RES promotion in deregulated powermarkets,particularly within transmission systems.Furthermore,the optimal location and sizing of REGs in both balanced and unbalanced distribution systems have been extensively studied.RESs demonstrate significant potential for standalone applications in remote areas lacking conventional transmission and distribution infrastructure.Also presents a thorough review of current modeling and optimization approaches for RES-based distribution system location and sizing.Additionally,it examines the optimal positioning,sizing,and performance of hybrid and standalone renewable energy systems.This paper provides a comprehensive review of current modeling and optimization approaches for the location and sizing of Renewable Energy Sources(RESs)in distribution systems,focusing on both balanced and unbalanced networks.
基金supported by the National Key R&D Program of China(2022ZD0119604)the National Natural Science Foundation of China(NSFC)(62173181,62222308,62221004)the Natural Science Foundation of Jiangsu Province(BK20220139)
文摘This paper designs distributed Nash equilibrium seeking strategies for heterogeneous dynamic cyber-physical systems.In particular, we are concerned with parametric uncertainties in the control channel of the players. Moreover, the weights on communication links can be compromised by time-varying uncertainties, which can result from possibly malicious attacks,faults and disturbances. To deal with the unavailability of measurement of optimization errors, an output observer is constructed,based on which adaptive laws are designed to compensate for physical uncertainties. With adaptive laws, a new distributed Nash equilibrium seeking strategy is designed by further integrating consensus protocols and gradient search algorithms.Moreover, to further accommodate compromised communication weights resulting from cyber-uncertainties, the coupling strengths of the consensus module are designed to be adaptive. As a byproduct, the coupling strengths are independent of any global information. With theoretical investigations, it is proven that the proposed strategies are resilient to these uncertainties and players' actions are convergent to the Nash equilibrium. Simulation examples are given to numerically validate the effectiveness of the proposed strategies.
