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
In this paper,the distributed optimal formation control problem of heterogeneous Euler–Lagrange multi-agent systems with generic formation constraints and inequality constraints is investigated.Based on the primal–d...In this paper,the distributed optimal formation control problem of heterogeneous Euler–Lagrange multi-agent systems with generic formation constraints and inequality constraints is investigated.Based on the primal–dual dynamics and the adaptive control technique,a distributed optimal formation controller consists of a velocity reference signal generator and a velocity tracking controller is proposed.By using the optimality condition,the relationship between the equilibrium point of the closed-loop system and the optimal solution of the optimization problem is established.Then,by utilizing Lyapunov stability analysis,it is rigorously proved that the optimal formation is reached with the proposed controller.Lastly,simulation examples are provided to substantiate the theoretical results.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
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
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
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,Through distributed machine learning,multi-UAV systems can achieve global optimization goals without a centralized server,such as optimal target tracking,by leveraging local calculation and communication w...Dear Editor,Through distributed machine learning,multi-UAV systems can achieve global optimization goals without a centralized server,such as optimal target tracking,by leveraging local calculation and communication with neighbors.In this work,we implement the stochastic gradient descent algorithm(SGD)distributedly to optimize tracking errors based on local state and aggregation of the neighbors'estimation.However,Byzantine agents can mislead neighbors,causing deviations from optimal tracking.We prove that the swarm achieves resilient convergence if aggregated results lie within the normal neighbors'convex hull,which can be guaranteed by the introduced centerpoint-based aggregation rule.In the given simulated scenarios,distributed learning using average,geometric median(GM),and coordinate-wise median(CM)based aggregation rules fail to track the target.Compared to solely using the centerpoint aggregation method,our approach,which combines a pre-filter with the centroid aggregation rule,significantly enhances resilience against Byzantine attacks,achieving faster convergence and smaller tracking errors.展开更多
Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decrypt...Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.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
Dear Editor,This letter studies a real-world issue in leader-follower multi-agent systems(MASs)named open topology,which permits the variations of agent set and network connections.Specially,a novel transition process...Dear Editor,This letter studies a real-world issue in leader-follower multi-agent systems(MASs)named open topology,which permits the variations of agent set and network connections.Specially,a novel transition process is developed to explain how the involved variation of network scale affects the dynamic behavior of the MASs.From a resource limited perspective,the distributed saturated impulsive control is then designed,under which some sufficient criteria are integrated into local quasi-consensus performance.We also provide a combined optimization algorithm for all agents to make the estimated domain of initial errors closer to the real one,thereby resulting in less conservativeness.Finally,a numerical example validates our results.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
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
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
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
In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the intera...In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the interaction topology is undirected and connected and the unknown nonlinear uncertain dynamics can be parameterized by a neural network, an adaptive learning law is proposed to deal with unknown nonlinear dynamics, based on which a kind of cooperative tracking protocols are constructed. The feedback gain matrix is obtained to solve an algebraic Riccati equation. To construct the fully distributed cooperative tracking protocols, the adaptive law is also adopted to adjust the coupling weight. With the developed control laws,we can prove that all signals in the closed-loop systems are guaranteed to be uniformly ultimately bounded. Finally, a simple simulation example is provided to illustrate the established result.展开更多
Based on the idea of backstepping design, distributedcoordinated tracking problems under directed topology are discussedfor multiple Euler-Lagrange （EL） systems. The dynamicleader case is considered. First, with the...Based on the idea of backstepping design, distributedcoordinated tracking problems under directed topology are discussedfor multiple Euler-Lagrange （EL） systems. The dynamicleader case is considered. First, with the parameter-linearity property,a distributed coordinated adaptive control scheme is proposedfor EL systems in the presence of parametric uncertainties.Then, subject to nonlinear uncertainties and external disturbances,an improved adaptive control algorithm is developed by usingneural-network （NN） approximation of nonlinear functions. Bothproposed algorithms can make tracking errors for each followerultimately bounded. The closed-loop systems are investigated byusing the combination of graph theory, Lyapunov theory, and BarbalatLemma. Numerical examples and comparisons with othermethods are provided to show the effectiveness of the proposedcontrol strategies.展开更多
Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of...Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.展开更多
The exponential stabilization problem for finite dimensional switched systems is extended to the infinite dimensional distributed parameter systems in the Hilbert space. Based on the semigroup theory, by applying the ...The exponential stabilization problem for finite dimensional switched systems is extended to the infinite dimensional distributed parameter systems in the Hilbert space. Based on the semigroup theory, by applying the multiple Lyapunov function method, the exponential stabilization conditions are derived. These conditions are given in the form of linear operator inequalities where the decision variables are operators in the Hilbert space; while the stabilization properties depend on the switching rule. Being applied to the two-dimensional heat switched propagation equations with the Dirichlet boundary conditions, these linear operator inequalities are transformed into standard linear matrix inequalities. Finally, two examples are given to illustrate the effectiveness of the proposed results.展开更多
In this paper, delay-dependent robust stabilization and H∞ control for uncertain stochastic Takagi-Sugeno （T-S） fuzzy systems with discrete interval and distributed time-varying delays are discussed. The purpose of...In this paper, delay-dependent robust stabilization and H∞ control for uncertain stochastic Takagi-Sugeno （T-S） fuzzy systems with discrete interval and distributed time-varying delays are discussed. The purpose of the robust stochastic stabilization problem is to design a memoryless state feedback controller such that the closed-loop system is mean-square asymptotically stable for all admissible uncertainties. In the robust H∞ control problem, in addition to the mean-square asymptotic stability requirement, a prescribed H∞ performance is required to be achieved. Sufficient conditions for the solvability of these problems are proposed in terms of a set of linear matrix inequalities （LMIs） and solving these LMIs, a desired controller can be obtained. Finally, two numerical examples are given to illustrate the effectiveness and less conservativeness of our results over the existing ones.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supported in part by the National Key Research and Development Program of China under Grant 2022YFB3303900in part by the National Natural Science Foundation of China under Grants 62103277 and 62025305。
文摘In this paper,the distributed optimal formation control problem of heterogeneous Euler–Lagrange multi-agent systems with generic formation constraints and inequality constraints is investigated.Based on the primal–dual dynamics and the adaptive control technique,a distributed optimal formation controller consists of a velocity reference signal generator and a velocity tracking controller is proposed.By using the optimality condition,the relationship between the equilibrium point of the closed-loop system and the optimal solution of the optimization problem is established.Then,by utilizing Lyapunov stability analysis,it is rigorously proved that the optimal formation is reached with the proposed controller.Lastly,simulation examples are provided to substantiate the theoretical results.
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.
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.
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 Guangdong Major Project of Basic and Applied Basic Research(2023B0303000009)Guangdong Basic and Applied Basic Research Foundation(2024A1515030153,2025A1515011587)+1 种基金Project of Department of Education of Guangdong Province(2023ZDZX4046)Shen-zhen Natural Science Fund(Stable Support Plan Program 20231122121608001),Ningbo Municipal Science and Technology Bureau(ZX2024000604).
文摘Dear Editor,Through distributed machine learning,multi-UAV systems can achieve global optimization goals without a centralized server,such as optimal target tracking,by leveraging local calculation and communication with neighbors.In this work,we implement the stochastic gradient descent algorithm(SGD)distributedly to optimize tracking errors based on local state and aggregation of the neighbors'estimation.However,Byzantine agents can mislead neighbors,causing deviations from optimal tracking.We prove that the swarm achieves resilient convergence if aggregated results lie within the normal neighbors'convex hull,which can be guaranteed by the introduced centerpoint-based aggregation rule.In the given simulated scenarios,distributed learning using average,geometric median(GM),and coordinate-wise median(CM)based aggregation rules fail to track the target.Compared to solely using the centerpoint aggregation method,our approach,which combines a pre-filter with the centroid aggregation rule,significantly enhances resilience against Byzantine attacks,achieving faster convergence and smaller tracking errors.
基金supported by the National Natural Science Foundation of China(12471416,12171124,12301567)the Heilongjiang Provincial Natural Science Foundation of China(PL2024F015)+2 种基金the Postdoctoral Science Foundation of Heilongjiang Province of China(LBH-Z22199)the Fundamental Research Foun-dation for Universities of Heilongjiang Province of China(2022-KYYWF-0141)the Alexander von Humboldt Foundation of Germany.
文摘Dear Editor,This letter deals with the distributed recursive set-membership filtering(DRSMF)issue for state-saturated systems under encryption-decryption mechanism.To guarantee the data security,the encryption-decryption mechanism is considered in the signal transmission process.Specifically,a novel DRSMF scheme is developed such that,for both state saturation and encryption-decryption mechanism,the filtering error(FE)is limited to the ellipsoid domain.Then,the filtering error constraint matrix(FECM)is computed and a desirable filter gain is derived by minimizing the FECM.Besides,the bound-edness evaluation of the FECM is provided.
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.
基金supported by the Natural Science Foundation of Jiangsu Province(BK20240009)the National Natural Science Foundation of China(62373105,62373262)Jiangsu Provincial Scientific Research Center of Applied Mathematics(BK20233002).
文摘Dear Editor,This letter studies a real-world issue in leader-follower multi-agent systems(MASs)named open topology,which permits the variations of agent set and network connections.Specially,a novel transition process is developed to explain how the involved variation of network scale affects the dynamic behavior of the MASs.From a resource limited perspective,the distributed saturated impulsive control is then designed,under which some sufficient criteria are integrated into local quasi-consensus performance.We also provide a combined optimization algorithm for all agents to make the estimated domain of initial errors closer to the real one,thereby resulting in less conservativeness.Finally,a numerical example validates our results.
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.
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.
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 National Natural Science Foundation of China(61303211)Zhejiang Provincial Natural Science Foundation of China(LY17F030003,LY15F030009)
文摘In this paper, the leader-following tracking problem of fractional-order multi-agent systems is addressed. The dynamics of each agent may be heterogeneous and has unknown nonlinearities. By assumptions that the interaction topology is undirected and connected and the unknown nonlinear uncertain dynamics can be parameterized by a neural network, an adaptive learning law is proposed to deal with unknown nonlinear dynamics, based on which a kind of cooperative tracking protocols are constructed. The feedback gain matrix is obtained to solve an algebraic Riccati equation. To construct the fully distributed cooperative tracking protocols, the adaptive law is also adopted to adjust the coupling weight. With the developed control laws,we can prove that all signals in the closed-loop systems are guaranteed to be uniformly ultimately bounded. Finally, a simple simulation example is provided to illustrate the established result.
基金supported by the National Natural Science Foundation of China(6130400561174200)the Research Fund for the Doctoral Program of Higher Education of China(20102302110031)
文摘Based on the idea of backstepping design, distributedcoordinated tracking problems under directed topology are discussedfor multiple Euler-Lagrange （EL） systems. The dynamicleader case is considered. First, with the parameter-linearity property,a distributed coordinated adaptive control scheme is proposedfor EL systems in the presence of parametric uncertainties.Then, subject to nonlinear uncertainties and external disturbances,an improved adaptive control algorithm is developed by usingneural-network （NN） approximation of nonlinear functions. Bothproposed algorithms can make tracking errors for each followerultimately bounded. The closed-loop systems are investigated byusing the combination of graph theory, Lyapunov theory, and BarbalatLemma. Numerical examples and comparisons with othermethods are provided to show the effectiveness of the proposedcontrol strategies.
基金Project (Nos. 60074011 and 60574049) supported by the National Natural Science Foundation of China
文摘Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.
基金The National Natural Science Foundation of China(No.61273119,61104068,61374038)the Natural Science Foundation of Jiangsu Province(No.BK2011253)
文摘The exponential stabilization problem for finite dimensional switched systems is extended to the infinite dimensional distributed parameter systems in the Hilbert space. Based on the semigroup theory, by applying the multiple Lyapunov function method, the exponential stabilization conditions are derived. These conditions are given in the form of linear operator inequalities where the decision variables are operators in the Hilbert space; while the stabilization properties depend on the switching rule. Being applied to the two-dimensional heat switched propagation equations with the Dirichlet boundary conditions, these linear operator inequalities are transformed into standard linear matrix inequalities. Finally, two examples are given to illustrate the effectiveness of the proposed results.
文摘In this paper, delay-dependent robust stabilization and H∞ control for uncertain stochastic Takagi-Sugeno （T-S） fuzzy systems with discrete interval and distributed time-varying delays are discussed. The purpose of the robust stochastic stabilization problem is to design a memoryless state feedback controller such that the closed-loop system is mean-square asymptotically stable for all admissible uncertainties. In the robust H∞ control problem, in addition to the mean-square asymptotic stability requirement, a prescribed H∞ performance is required to be achieved. Sufficient conditions for the solvability of these problems are proposed in terms of a set of linear matrix inequalities （LMIs） and solving these LMIs, a desired controller can be obtained. Finally, two numerical examples are given to illustrate the effectiveness and less conservativeness of our results over the existing ones.
