This article investigates the issue of finite-time state estimation in coupled neural networks under random mixed cyberattacks,in which the Markov process is used to model the mixed cyberattacks.To optimize the utiliz...This article investigates the issue of finite-time state estimation in coupled neural networks under random mixed cyberattacks,in which the Markov process is used to model the mixed cyberattacks.To optimize the utilization of channel resources,a decentralized event-triggered mechanism is adopted during the information transmission.By establishing the augmentation system and constructing the Lyapunov function,sufficient conditions are obtained for the system to be finite-time bounded and satisfy the H_(∞ )performance index.Then,under these conditions,a suitable state estimator gain is obtained.Finally,the feasibility of the method is verified by a given illustrative example.展开更多
This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,t...This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.展开更多
This paper concerns the decentralized event-based H_(∞)filter design problem for networked dynamic system(NDS).A more practical situation is studied,in which the communication between subsystems is affected by uncert...This paper concerns the decentralized event-based H_(∞)filter design problem for networked dynamic system(NDS).A more practical situation is studied,in which the communication between subsystems is affected by uncertainties and only local sampled measurement output is available for each filter in the developed filter scheme.Firstly,an event-triggered mechanism is introduced for each subsystem to process the sampled output in order to reduce the communication load.Secondly,on the basis of the well-posedness,the augmented filtering error system composed of the original NDS and the filter is modeled as a time-delay system of high dimension.After that,by employing the Lyapunov functional approach and space construction method,novel computationally attractive sufficient conditions are derived to check the well-posedness,asymptotic stability and H_(∞)performance of the augmented filtering error system.Thirdly,a co-design method of the filter and event-trigger matrices is obtained by using Finsler lemma and slack matrix approach.Finally,a numerical example is provided to demonstrate the effectiveness of the derived design approach.展开更多
Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combinin...Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.展开更多
To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance dat...To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.展开更多
This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main ob...This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system. First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established. Second,a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner. In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy. Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived. Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach. It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency.展开更多
This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method...This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.展开更多
Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study...Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.展开更多
The event-triggered mechanism serves as an effective discontinuous control strategy for addressing the consensus tracking problem in multiagent systems(MASs).This approach optimizes energy consumption by updating the ...The event-triggered mechanism serves as an effective discontinuous control strategy for addressing the consensus tracking problem in multiagent systems(MASs).This approach optimizes energy consumption by updating the controller only when some observed errors exceed a predefined threshold.Considering the influence of noise on agent dynamics in complex control environments,this study investigates an event-triggered control scheme for stochastic MASs,where noise is modeled as Brownian motion.Furthermore,the communication topology of the stochastic MASs is assumed to exhibit a Markovian switching mechanism.Analytical criteria are derived to guarantee consensus tracking in the mean square sense,and a numerical example is provided to validate the effectiveness of the proposed control methods.展开更多
Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has bee...Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has been advocated for decentralized data management in a tamper-resistance,traceable,and transparent manner.However,a major issue that hinders the integration of blockchain and IoT lies in that,it is rather challenging for resource-constrained IoT devices to perform computation-intensive blockchain consensuses such as Proof-of-Work(PoW).Furthermore,the incentive mechanism of PoW pushes lightweight IoT nodes to aggregate their computing power to increase the possibility of successful block generation.Nevertheless,this eventually leads to the formation of computing power alliances,and significantly compromises the decentralization and security of BlockChain-aided IoT(BC-IoT)networks.To cope with these issues,we propose a lightweight consensus protocol for BC-IoT,called Proof-of-Trusted-Work(PoTW).The goal of the proposed consensus is to disincentivize the centralization of computing power and encourage the independent participation of lightweight IoT nodes in blockchain consensus.First,we put forth an on-chain reputation evaluation rule and a reputation chain for PoTW to enable the verifiability and traceability of nodes’reputations based on their contributions of computing power to the blockchain consensus,and we incorporate the multi-level block generation difficulty as a rewards for nodes to accumulate reputations.Second,we model the block generation process of PoTW and analyze the block throughput using the continuous time Markov chain.Additionally,we define and optimize the relative throughput gain to quantify and maximize the capability of PoTW that suppresses the computing power centralization(i.e.,centralization suppression).Furthermore,we investigate the impact of the computing power of the computing power alliance and the levels of block generation difficulty on the centralization suppression capability of PoTW.Finally,simulation results demonstrate the consistency of the analytical results in terms of block throughput.In particular,the results show that PoTW effectively reduces the block generation proportion of the computing power alliance compared with PoW,while simultaneously improving that of individual lightweight nodes.This indicates that PoTW is capable of suppressing the centralization of computing power to a certain degree.Moreover,as the levels of block generation difficulty in PoTW increase,its centralization suppression capability strengthens.展开更多
This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-...This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-differentiable and in turn can be fast-varying.Moreover,the systems admit unknown control directions.To counteract the different uncertainties,more than one compensation mechanism has to be incorporated.However,in the context of event-triggered control,ensuring the effectiveness of these compensation mechanisms under reduced execution necessitates delicate design and analysis.This paper proposes a tight and powerful strategy for adaptive event-triggered control(ETC)by integrating the state-of-the-art adaptive techniques.In particular,the strategy substantially mitigates the conservatism caused by repetitive inequality-based treatments of uncertainties.Specifically,by leveraging the congelation-of-variables method and tuning functions,the conservatism in the treatment of the fast-varying parameters is significantly reduced.With multiple Nussbaum functions employed to handle unknown control directions,a set of dynamic compensations is designed to counteract unknown amplitudes of control coefficients without relying on inequality-based treatments.Moreover,a dedicated dynamic compensation is introduced to deal with the control coefficient coupled with the execution error,based on which a relativethreshold event-triggering mechanism(ETM)is rigorously validated.It turns out that the adaptive event-triggered controller achieves the closed-loop convergence while guaranteeing a uniform lower bound for inter-execution times.Simulation results verify the effectiveness and superiority of the proposed strategy.展开更多
Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and acc...Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.展开更多
This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires t...This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.展开更多
This paper is concerned with event-triggered control of discrete-time systems with or without input saturation.First,an accumulative-error-based event-triggered scheme is devised for control updates.When the accumulat...This paper is concerned with event-triggered control of discrete-time systems with or without input saturation.First,an accumulative-error-based event-triggered scheme is devised for control updates.When the accumulated error between the current state and the latest control update exceeds a certain threshold,an event is triggered.Such a scheme can ensure the event-generator works at a relatively low rate rather than falls into hibernation especially after the system steps into its steady state.Second,the looped functional method for continuous-time systems is extended to discrete-time systems.By introducing an innovative looped functional that links the event-triggered scheme,some sufficient conditions for the co-design of control gain and event-triggered parameters are obtained in terms of linear matrix inequalities with a couple of tuning parameters.Then,the proposed method is applied to discrete-time systems with input saturation.As a result,both suitable control gains and event-triggered parameters are also co-designed to ensure the system trajectories converge to the region of attraction.Finally,an unstable reactor system and an inverted pendulum system are given to show the effectiveness of the proposed method.展开更多
In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy.In classical federated learning, the...In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy.In classical federated learning, the communication channel between the devices poses a potential risk of compromising private information. To reduce the risk of adversary eavesdropping in the communication channel, we propose TRADE(transmit difference weight) concept. This concept replaces the decentralized federated learning algorithm's transmitted weight parameters with differential weight parameters, enhancing the privacy data against eavesdropping. Subsequently, by integrating the TRADE concept with the primal-dual stochastic gradient descent(SGD)algorithm, we propose a decentralized TRADE primal-dual SGD algorithm. We demonstrate that our proposed algorithm's convergence properties are the same as those of the primal-dual SGD algorithm while providing enhanced privacy protection. We validate the algorithm's performance on fault diagnosis task using the Case Western Reserve University dataset, and image classification tasks using the CIFAR-10 and CIFAR-100 datasets,revealing model accuracy comparable to centralized federated learning. Additionally, the experiments confirm the algorithm's privacy protection capability.展开更多
Federated Graph Learning (FGL) enables model training without requiring each client to share local graph data, effectively breaking data silos by aggregating the training parameters from each terminal while safeguardi...Federated Graph Learning (FGL) enables model training without requiring each client to share local graph data, effectively breaking data silos by aggregating the training parameters from each terminal while safeguarding data privacy. Traditional FGL relies on a centralized server for model aggregation;however, this central server presents challenges such as a single point of failure and high communication overhead. Additionally, efficiently training a robust personalized local model for each client remains a significant objective in federated graph learning. To address these issues, we propose a decentralized Federated Graph Learning framework with efficient communication, termed Decentralized Federated Graph Learning via Surrogate Model (SD_FGL). In SD_FGL, each client is required to maintain two models: a private model and a surrogate model. The surrogate model is publicly shared and can exchange and update information directly with any client, eliminating the need for a central server and reducing communication overhead. The private model is independently trained by each client, allowing it to calculate similarity with other clients based on local data as well as information shared through the surrogate model. This enables the private model to better adjust its training strategy and selectively update its parameters. Additionally, local differential privacy is incorporated into the surrogate model training process to enhance privacy protection. Testing on three real-world graph datasets demonstrates that the proposed framework improves accuracy while achieving decentralized Federated Graph Learning with lower communication overhead and stronger privacy safeguards.展开更多
Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track pred...Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.展开更多
Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the ...Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the predicament by evaluating the feasibility of renewable energy-based decentralized electrification in the selected village ofDoleibHill,UpperNile,South Sudan.Using a demand assessment and theMulti-Tier Framework(MTF)approach,it categorizes households,public facilities,private sector,Non-GovernmentalOrganizations(NGOs)and business energy needs and designs an optimized hybrid energy system incorporating solar Photovoltaic(PV),wind turbines,batteries,and a generator.The proposed system,simulated in Hybrid Optimization Model Electric Renewable(HOMER)Pro,demonstrates strong economic viability,with a present worth of$292,145,an annual worth of$22,854,a return on investment(ROI)of 36.5%,and an internal rate of return(IRR)of 42.1%.The simple payback period is 2.31 years,and the discounted payback period is 2.62 years.The system achieves a levelized cost of energy(LCOE)of$0.276/kWh and significantly reduces dependence on diesel,producing 798,800 kWh annually fromwind energy.This research provides a replicable model for cost-effective,sustainable rural electrification,offering valuable insights for policymakers and energy planners seeking to expand electricity access in off-grid communities.展开更多
This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems posses...This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.62303016)the Research and Development Project of Engineering Research Center of Biofilm Water Purification and Utilization Technology of the Ministry of Education of China(Grant No.BWPU2023ZY02)+1 种基金the University Synergy Innovation Program of Anhui Province,China(Grant No.GXXT-2023-020)the Key Project of Natural Science Research in Universities of Anhui Province,China(Grant No.2024AH050171).
文摘This article investigates the issue of finite-time state estimation in coupled neural networks under random mixed cyberattacks,in which the Markov process is used to model the mixed cyberattacks.To optimize the utilization of channel resources,a decentralized event-triggered mechanism is adopted during the information transmission.By establishing the augmentation system and constructing the Lyapunov function,sufficient conditions are obtained for the system to be finite-time bounded and satisfy the H_(∞ )performance index.Then,under these conditions,a suitable state estimator gain is obtained.Finally,the feasibility of the method is verified by a given illustrative example.
基金supported by National Natural Science Foundation of China(61473182)National Key Scientific Instrument and Equipment Development Project(2012YQ15008703)+1 种基金Project of Science and Technology Commission of Shanghai Municipality(14JC1402200,15JC1401900,14ZR1414800)Shanghai Rising-Star Program(13QA1401600)
基金supported by the National Natural Science Foundation of China(U21A20477,61722302,61573069,61903290)the Fundamental Research Funds for the Central Universities(DUT19ZD218).
文摘This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.
基金supported by Hebei Natural Science Foundation under Grant Nos.A2023203044 and F2022203097the National Natural Science Foundation of China under Grant Nos.12201451 and 62203377+3 种基金the Changzhou Sci&Tech Program under Grant No.CJ20235012the Science Research Project of Hebei Education Department under Grant No.QN2022077the S&T Program of Hebei under Grant No.236Z1603Gthe Yanshan University Basic Innovation Scientific Research Cultivation Project(Youth Project)under Grant No.2024LGQN015。
文摘This paper concerns the decentralized event-based H_(∞)filter design problem for networked dynamic system(NDS).A more practical situation is studied,in which the communication between subsystems is affected by uncertainties and only local sampled measurement output is available for each filter in the developed filter scheme.Firstly,an event-triggered mechanism is introduced for each subsystem to process the sampled output in order to reduce the communication load.Secondly,on the basis of the well-posedness,the augmented filtering error system composed of the original NDS and the filter is modeled as a time-delay system of high dimension.After that,by employing the Lyapunov functional approach and space construction method,novel computationally attractive sufficient conditions are derived to check the well-posedness,asymptotic stability and H_(∞)performance of the augmented filtering error system.Thirdly,a co-design method of the filter and event-trigger matrices is obtained by using Finsler lemma and slack matrix approach.Finally,a numerical example is provided to demonstrate the effectiveness of the derived design approach.
文摘Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.
基金supported in part by the National Natural Science Foundation of China,Grant/Award Number:62003267the Key Research and Development Program of Shaanxi Province,Grant/Award Number:2023-GHZD-33Open Project of the State Key Laboratory of Intelligent Game,Grant/Award Number:ZBKF-23-05。
文摘To address the issue of instability or even imbalance in the orientation and attitude control of quadrotor unmanned aerial vehicles(QUAVs)under random disturbances,this paper proposes a distributed antidisturbance data-driven event-triggered fusion control method,which achieves efficient fault diagnosis while suppressing random disturbances and mitigating communication conflicts within the QUAV swarm.First,the impact of random disturbances on the UAV swarm is analyzed,and a model for orientation and attitude control of QUAVs under stochastic perturbations is established,with the disturbance gain threshold determined.Second,a fault diagnosis system based on a high-gain observer is designed,constructing a fault gain criterion by integrating orientation and attitude information from QUAVs.Subsequently,a model-free dynamic linearization-based data modeling(MFDLDM)framework is developed using model-free adaptive control,which efficiently fits the nonlinear control model of the QUAV swarm while reducing temporal constraints on control data.On this basis,this paper constructs a distributed data-driven event-triggered controller based on the staggered communication mechanism,which consists of an equivalent QUAV controller and an event-triggered controller,and is able to reduce the communication conflicts while suppressing the influence of random interference.Finally,by incorporating random disturbances into the controller,comparative experiments and physical validations are conducted on the QUAV platforms,fully demonstrating the strong adaptability and robustness of the proposed distributed event-triggered fault-tolerant control system.
文摘This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system. First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established. Second,a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner. In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy. Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived. Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach. It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency.
基金The National Natural Science Foundation of China(W2431048)The Science and Technology Research Program of Chongqing Municipal Education Commission,China(KJZDK202300807)The Chongqing Natural Science Foundation,China(CSTB2024NSCQQCXMX0052).
文摘This paper addresses the consensus problem of nonlinear multi-agent systems subject to external disturbances and uncertainties under denial-ofservice(DoS)attacks.Firstly,an observer-based state feedback control method is employed to achieve secure control by estimating the system's state in real time.Secondly,by combining a memory-based adaptive eventtriggered mechanism with neural networks,the paper aims to approximate the nonlinear terms in the networked system and efficiently conserve system resources.Finally,based on a two-degree-of-freedom model of a vehicle affected by crosswinds,this paper constructs a multi-unmanned ground vehicle(Multi-UGV)system to validate the effectiveness of the proposed method.Simulation results show that the proposed control strategy can effectively handle external disturbances such as crosswinds in practical applications,ensuring the stability and reliable operation of the Multi-UGV system.
基金supported by the National Research Foundation of Korea(NRF)grants(2022R1A2C4001228,2022M3H4A4097524,2022M3I3A1082499,and 2021M3I3A1084818)the Technology Innovation Program(20026415)of the Ministry of Trade,Industry&Energy(MOTIE,Korea)the supports from Nanopac for fabrication of scaled-up reactor.
文摘Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.
文摘The event-triggered mechanism serves as an effective discontinuous control strategy for addressing the consensus tracking problem in multiagent systems(MASs).This approach optimizes energy consumption by updating the controller only when some observed errors exceed a predefined threshold.Considering the influence of noise on agent dynamics in complex control environments,this study investigates an event-triggered control scheme for stochastic MASs,where noise is modeled as Brownian motion.Furthermore,the communication topology of the stochastic MASs is assumed to exhibit a Markovian switching mechanism.Analytical criteria are derived to guarantee consensus tracking in the mean square sense,and a numerical example is provided to validate the effectiveness of the proposed control methods.
基金supported in part by National Key R&D Program of China(Grant No.2021YFB1714100)in part by the National Natural Science Foundation of China(NSFC)under Grant 62371239+5 种基金in part by the the Program of Science and Technology Cooperation of Nanjing with International/Hong Kong,Macao and Taiwan(Grant No.202401019)in part by the Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515012407)in part by the the Research Center for FinTech and Digital-Intelligent Management at Shenzhen University,in part by the National Natural Science Foundation of China under Grant 62271192in part by the Equipment Pre-Research Joint Research Program of Ministry of Education under Grant 8091B032129in part by the Major Science and Technology Projects of Longmen Laboratory under Grant 231100220300 and 231100220200in part by the Central Plains Leading Talent in Scientific and Technological Innovation Program under Grant 244200510048.
文摘Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has been advocated for decentralized data management in a tamper-resistance,traceable,and transparent manner.However,a major issue that hinders the integration of blockchain and IoT lies in that,it is rather challenging for resource-constrained IoT devices to perform computation-intensive blockchain consensuses such as Proof-of-Work(PoW).Furthermore,the incentive mechanism of PoW pushes lightweight IoT nodes to aggregate their computing power to increase the possibility of successful block generation.Nevertheless,this eventually leads to the formation of computing power alliances,and significantly compromises the decentralization and security of BlockChain-aided IoT(BC-IoT)networks.To cope with these issues,we propose a lightweight consensus protocol for BC-IoT,called Proof-of-Trusted-Work(PoTW).The goal of the proposed consensus is to disincentivize the centralization of computing power and encourage the independent participation of lightweight IoT nodes in blockchain consensus.First,we put forth an on-chain reputation evaluation rule and a reputation chain for PoTW to enable the verifiability and traceability of nodes’reputations based on their contributions of computing power to the blockchain consensus,and we incorporate the multi-level block generation difficulty as a rewards for nodes to accumulate reputations.Second,we model the block generation process of PoTW and analyze the block throughput using the continuous time Markov chain.Additionally,we define and optimize the relative throughput gain to quantify and maximize the capability of PoTW that suppresses the computing power centralization(i.e.,centralization suppression).Furthermore,we investigate the impact of the computing power of the computing power alliance and the levels of block generation difficulty on the centralization suppression capability of PoTW.Finally,simulation results demonstrate the consistency of the analytical results in terms of block throughput.In particular,the results show that PoTW effectively reduces the block generation proportion of the computing power alliance compared with PoW,while simultaneously improving that of individual lightweight nodes.This indicates that PoTW is capable of suppressing the centralization of computing power to a certain degree.Moreover,as the levels of block generation difficulty in PoTW increase,its centralization suppression capability strengthens.
基金supported in part by the National Natural Science Foundation of China(62033007)the Fundamental Research Program of Shandong Province(ZR2023ZD37).
文摘This paper considers adaptive event-triggered stabilization for a class of uncertain time-varying nonlinear systems.Remarkably,the systems contain intrinsic time-varying unknown parameters which are allowed to be non-differentiable and in turn can be fast-varying.Moreover,the systems admit unknown control directions.To counteract the different uncertainties,more than one compensation mechanism has to be incorporated.However,in the context of event-triggered control,ensuring the effectiveness of these compensation mechanisms under reduced execution necessitates delicate design and analysis.This paper proposes a tight and powerful strategy for adaptive event-triggered control(ETC)by integrating the state-of-the-art adaptive techniques.In particular,the strategy substantially mitigates the conservatism caused by repetitive inequality-based treatments of uncertainties.Specifically,by leveraging the congelation-of-variables method and tuning functions,the conservatism in the treatment of the fast-varying parameters is significantly reduced.With multiple Nussbaum functions employed to handle unknown control directions,a set of dynamic compensations is designed to counteract unknown amplitudes of control coefficients without relying on inequality-based treatments.Moreover,a dedicated dynamic compensation is introduced to deal with the control coefficient coupled with the execution error,based on which a relativethreshold event-triggering mechanism(ETM)is rigorously validated.It turns out that the adaptive event-triggered controller achieves the closed-loop convergence while guaranteeing a uniform lower bound for inter-execution times.Simulation results verify the effectiveness and superiority of the proposed strategy.
基金Fundação de AmparoàPesquisa do Estado da Bahia(FAPESB),Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico(CNPq)organizations for supporting the Graduate Program in Computer Science at the Federal University of Bahia.
文摘Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.
基金supported by the National Natural Science Foundation of China under Grant 62073190the Science Center Program of National Natural Science Foundation of China under Grant 62188101.
文摘This paper investigates the problem of dynamic event-triggered control for a class of large-scale nonlinear systems.In particular,both neutral delays and unknown backlash-like hysteresis are considered.This requires to integrate a compensation mechanism into the event-triggered control architecture.To this end,dynamic gain and adaptive control techniques are introduced to address the effects of neutral delays,unknown hysteresis and parameter uncertainties simultaneously.By introducing a non-negative internal dynamic variable,a dynamic event-triggered controller is designed using the hyperbolic tangent function to reduce the communication burden.By means of the Lyapunov–Krasovskii method,it is demonstrated that all signals of the closed-loop system are globally bounded and eventually converge to a tunable bounded region.Moreover,the Zeno behavior is avoided.Finally,a simulation example is presented to verify the validity of the control scheme.
基金supported in part by the National Natural Science Foundation of China(62473221)the Natural Science Foundation of Shandong Province,China(ZR2024MF006)Qingdao Natural Science Foundation(24-4-4-zrjj-165-jch)。
文摘This paper is concerned with event-triggered control of discrete-time systems with or without input saturation.First,an accumulative-error-based event-triggered scheme is devised for control updates.When the accumulated error between the current state and the latest control update exceeds a certain threshold,an event is triggered.Such a scheme can ensure the event-generator works at a relatively low rate rather than falls into hibernation especially after the system steps into its steady state.Second,the looped functional method for continuous-time systems is extended to discrete-time systems.By introducing an innovative looped functional that links the event-triggered scheme,some sufficient conditions for the co-design of control gain and event-triggered parameters are obtained in terms of linear matrix inequalities with a couple of tuning parameters.Then,the proposed method is applied to discrete-time systems with input saturation.As a result,both suitable control gains and event-triggered parameters are also co-designed to ensure the system trajectories converge to the region of attraction.Finally,an unstable reactor system and an inverted pendulum system are given to show the effectiveness of the proposed method.
基金supported by the National Key Research and Development Program of China(2022YFB3305904)the National Natural Science Foundation of China(62133003,61991403,61991400)+4 种基金the Open Project of State Key Laboratory of Synthetical Automation for Process Industries(SAPI-2024-KFKT-05,SAPI-2024-KFKT-08)China Academy of Engineering Institute of Land Cooperation Consulting Project(2023-DFZD-60-02,N2424004)the Fundamental Research Funds for the Central UniversitiesShanghai Municipal Science and Technology Major Project(2021SHZDZX0100)the Key Research and Development Program of Liaoning Province(2023JH26/10200011)
文摘In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy.In classical federated learning, the communication channel between the devices poses a potential risk of compromising private information. To reduce the risk of adversary eavesdropping in the communication channel, we propose TRADE(transmit difference weight) concept. This concept replaces the decentralized federated learning algorithm's transmitted weight parameters with differential weight parameters, enhancing the privacy data against eavesdropping. Subsequently, by integrating the TRADE concept with the primal-dual stochastic gradient descent(SGD)algorithm, we propose a decentralized TRADE primal-dual SGD algorithm. We demonstrate that our proposed algorithm's convergence properties are the same as those of the primal-dual SGD algorithm while providing enhanced privacy protection. We validate the algorithm's performance on fault diagnosis task using the Case Western Reserve University dataset, and image classification tasks using the CIFAR-10 and CIFAR-100 datasets,revealing model accuracy comparable to centralized federated learning. Additionally, the experiments confirm the algorithm's privacy protection capability.
基金supported by InnerMongolia Natural Science Foundation Project(2021LHMS06003)Inner Mongolia University Basic Research Business Fee Project(114).
文摘Federated Graph Learning (FGL) enables model training without requiring each client to share local graph data, effectively breaking data silos by aggregating the training parameters from each terminal while safeguarding data privacy. Traditional FGL relies on a centralized server for model aggregation;however, this central server presents challenges such as a single point of failure and high communication overhead. Additionally, efficiently training a robust personalized local model for each client remains a significant objective in federated graph learning. To address these issues, we propose a decentralized Federated Graph Learning framework with efficient communication, termed Decentralized Federated Graph Learning via Surrogate Model (SD_FGL). In SD_FGL, each client is required to maintain two models: a private model and a surrogate model. The surrogate model is publicly shared and can exchange and update information directly with any client, eliminating the need for a central server and reducing communication overhead. The private model is independently trained by each client, allowing it to calculate similarity with other clients based on local data as well as information shared through the surrogate model. This enables the private model to better adjust its training strategy and selectively update its parameters. Additionally, local differential privacy is incorporated into the surrogate model training process to enhance privacy protection. Testing on three real-world graph datasets demonstrates that the proposed framework improves accuracy while achieving decentralized Federated Graph Learning with lower communication overhead and stronger privacy safeguards.
基金supported in part by the Guangdong Provincial Universities'Characteristic Innovation Project under Grant 2024KTSCX360in part by the Guangdong Educational Science Planning Project under Grant 2023GXJK837.
文摘Inspired by the collective behaviors observed in bird flocks and fish schools,this paper proposes a novel Decentralized Model Predictive Flocking Control(DMPFC)framework to enable UAV swarms to autonomously track predefined reference trajectories while avoiding collisions and maintaining a stable quasi[Math Processing Error]-lattice formation.Unlike traditional approaches that rely on switching between predefined swarm formations,this framework utilizes identical local interaction rules for each UAV,allowing them to dynamically adjust their control inputs based on the motion states of neighboring UAVs,external environmental factors,and the desired reference trajectory,thereby enabling the swarm to adapt its formation dynamically.Through iterative state updates,the UAVs achieve consensus,allowing the swarm to follow the reference trajectory while self-organizing into a cohesive and stable group structure.To enhance computational efficiency,the framework integrates a closed-form solution for the optimization process,enabling real-time implementation even on computationally constrained micro-quadrotors.Theoretical analysis demonstrates that the proposed method ensures swarm consensus,maintains desired inter-agent distances,and stabilizes the swarm formation.Extensive simulations and real-world experiments validate the approach’s effectiveness and practicality,demonstrating that the proposed method achieves velocity consensus within approximately 200 ms and forms a stable quasi[Math Processing Error]-lattice structure nearly ten times faster than traditional models,with trajectory tracking errors on the order of millimeters.This underscores its potential for robust and efficient UAV swarm coordination in complex scenarios.
文摘Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the predicament by evaluating the feasibility of renewable energy-based decentralized electrification in the selected village ofDoleibHill,UpperNile,South Sudan.Using a demand assessment and theMulti-Tier Framework(MTF)approach,it categorizes households,public facilities,private sector,Non-GovernmentalOrganizations(NGOs)and business energy needs and designs an optimized hybrid energy system incorporating solar Photovoltaic(PV),wind turbines,batteries,and a generator.The proposed system,simulated in Hybrid Optimization Model Electric Renewable(HOMER)Pro,demonstrates strong economic viability,with a present worth of$292,145,an annual worth of$22,854,a return on investment(ROI)of 36.5%,and an internal rate of return(IRR)of 42.1%.The simple payback period is 2.31 years,and the discounted payback period is 2.62 years.The system achieves a levelized cost of energy(LCOE)of$0.276/kWh and significantly reduces dependence on diesel,producing 798,800 kWh annually fromwind energy.This research provides a replicable model for cost-effective,sustainable rural electrification,offering valuable insights for policymakers and energy planners seeking to expand electricity access in off-grid communities.
基金supported by the fund of Beijing Municipal Commission of Education(KM202210017001 and 22019821001)the Natural Science Foundation of Henan Province(222300420253).
文摘This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.
