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
In this paper,we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances.The multi-agent system consists of multipl...In this paper,we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances.The multi-agent system consists of multiple heterogeneous linear systems as leader agents and multiple heterogeneous linear systems as follower agents.We design both the state feedback and output feedback control protocols for each follower agent.In particular,a distributed state observer is designed for each follower agent that estimates the state of each leader agent.In the output feedback case,state observer is also designed for each follower agent to estimate its own state.With these estimates,we design low gain-based distributed control protocols,parameterized in a scalar low gain parameter.It is shown that,for any bounded set of the initial conditions,these control protocols cause the follower agents to track the weighted average of the outputs of the leader agents as long as the value of the low gain parameter is tuned sufficiently small.Simulation results illustrate the validity of the theoretical results.展开更多
In distributed radar,most of existing radar networks operate in the tracking fusion mode which combines radar target tracks for a higher positioning accuracy.However,as the filtering covariance matrix indicating posit...In distributed radar,most of existing radar networks operate in the tracking fusion mode which combines radar target tracks for a higher positioning accuracy.However,as the filtering covariance matrix indicating positioning accuracy often occupies many bits,the communication cost from local sensors to the fusion is not always sufficiently low for some wireless communication chan-nels.This paper studies how to compress data for distributed tracking fusion algorithms.Based on the K-singular value decomposition(K-SVD)algorithm,a sparse coding algorithm is presented to sparsely represent the filtering covariance matrix.Then the least square quantization(LSQ)algo-rithm is used to quantize the data according to the statistical characteristics of the sparse coeffi-cients.Quantized results are then coded with an arithmetic coding method which can further com-press data.Numerical results indicate that this tracking data compression algorithm drops the com-munication bandwidth to 4%at the cost of a 16%root mean squared error(RMSE)loss.展开更多
Based on interpretations of the apatite fission track analysis data for 10 outcrop samples and forward modeling of confined fission track length distributions, the thermal history of rocks in the Shiwandashan basin ...Based on interpretations of the apatite fission track analysis data for 10 outcrop samples and forward modeling of confined fission track length distributions, the thermal history of rocks in the Shiwandashan basin and its adjacent area, southern China, has been qualitatively and semi quantitatively studied. The results reflect several features of the thermal history. Firstly, all the samples have experienced temperatures higher than 60-70 ℃. Secondly, the time that the basement strata (T 1 b ) on the northwestern side of the Shiwandashan basin were uplifted and exhumed to the unannealed upper crust (with a paleogeotemperature of below 60-70 ℃) is much earlier than the basement rocks ( γ 1 5) on the southeastern side of the basin. Thirdly, the thermal history of samples from the basin can be divided into six stages, i.e., the fast burial and heating stage (220-145 Ma), the transient cooling stage (145-135 Ma), the burial and heating stage (135-70 Ma), the rapid cooling stage (70-50 Ma), the relatively stable stage (50-20 Ma) and another rapid cooling stage (20 Ma to present).展开更多
The distributed tracking control problem for heterogeneous multi-agent systems with unknown system dynamics is investigated.The objective is to provide a data-driven distributed tracking control protocol that ensures ...The distributed tracking control problem for heterogeneous multi-agent systems with unknown system dynamics is investigated.The objective is to provide a data-driven distributed tracking control protocol that ensures tracking performance between agents and the leader.To this end,the concept of data informativity for matching conditions is introduced.Then,the data-based sufficient and necessary conditions to achieve state tracking are provided.Meanwhile,a data-driven parameterisation approach for designing the distributed tracking control protocol is given.Compared with previous results,the reference input is considered in the leader's dynamics,and the computational burden is reduced by solving a set of data-based equations and inequality constraints rather than iteration.Additionally,the developed results are still appropriate for handling the tracking control issue of the single linear system,and the current constraint that the reference system be stable is eased.Finally,two simulation examples are given to verify the proposed schemes'effectiveness.展开更多
We propose a distributed labeled multi-Bernoulli(LMB)filter based on an efficient label matching method.Conventional distributed LMB filter fusion has the premise that the labels among local densities have already bee...We propose a distributed labeled multi-Bernoulli(LMB)filter based on an efficient label matching method.Conventional distributed LMB filter fusion has the premise that the labels among local densities have already been matched.However,considering that the label space of each local posterior is independent,such a premise is not practical in many applications.To achieve distributed fusion practically,we propose an efficient label matching method derived from the divergence of arithmetic average(AA)mechanism,and subsequently label-wise LMB filter fusion is performed according to the matching results.Compared with existing label matching methods,this proposed method shows higher performance,especially in low detection probability scenarios.Moreover,to guarantee the consistency and completeness of the fusion outcome,the overall fusion procedure is designed into the following four stages:pre-fusion,label determination,posterior complement,and uniqueness check.The performance of the proposed label matching distributed LMB filter fusion is demonstrated in a challenging nonlinear bearings-only multi-target tracking(MTT)scenario.展开更多
In the real world,centralized tracking in a large-scale wireless sensor network (WSN) may not be feasible due to the possible failure of fusion centre and the large communication delay in forwarding measurement data t...In the real world,centralized tracking in a large-scale wireless sensor network (WSN) may not be feasible due to the possible failure of fusion centre and the large communication delay in forwarding measurement data to the fusion centre. Distributed target tracking techniques can be employed by tasking sensor nodes near to the target to perform sensing,target state estimation and selection of future tasking sensor nodes. In this paper,the development and implementation of a prototype ultrasonic WSN test-bed to demonstrate distributed target tracking using the Extended Kalman Filter (EKF) algorithm is described. In the test-bed,a mobile robot is used to simulate the moving target,and static/mobile sensor nodes are deployed to detect and track the target. The sensor nodes and robots are equipped with sonar and MICAZ to receive and process instructions. Experimental evaluation of a number of sensor scheduling schemes are reported which shows the superior tracking performance of our distributed competition based sensor scheduling scheme.展开更多
Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the pos...Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.展开更多
This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local...This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local estimates are not lost too much, the authors propose an optimal distributed fusion algorithm which is equivalent to the corresponding centralized Kalman filtering fusion with complete communications even if the process noise does exist. When this condition is not satisfied, based on the above global optimality result and sensor data compression, the authors propose a suboptimal distributed fusion algorithm. Numerical examples show that this suboptimal algorithm still works well and significantly better than the standard distributed Kalman filtering fusion subject to packet loss even if the process noise power is quite large.展开更多
Progress in development of multi-agent control is reviewed.Different approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic pers...Progress in development of multi-agent control is reviewed.Different approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic perspective.Attention is paid to the design of multi-agent systems via Laplacian dynamics,as well as the role of the graph Laplacian spectrum,the challenges of unbalanced digraphs,and consensus-based estimation of graph statistics.Some emergent issues,e.g.,distributed optimization,distributed average tracking,and distributed network games,are also reported,which have witnessed extensive development recently.There are over 200 references listed,mostly to recent contributions.展开更多
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.
基金supported in part by the National Natural Science Foundation of China(Nos.62022055,61973215).
文摘In this paper,we revisit the semi-global weighted output average tracking problem for a discrete-time multi-agent system subject to input saturation and external disturbances.The multi-agent system consists of multiple heterogeneous linear systems as leader agents and multiple heterogeneous linear systems as follower agents.We design both the state feedback and output feedback control protocols for each follower agent.In particular,a distributed state observer is designed for each follower agent that estimates the state of each leader agent.In the output feedback case,state observer is also designed for each follower agent to estimate its own state.With these estimates,we design low gain-based distributed control protocols,parameterized in a scalar low gain parameter.It is shown that,for any bounded set of the initial conditions,these control protocols cause the follower agents to track the weighted average of the outputs of the leader agents as long as the value of the low gain parameter is tuned sufficiently small.Simulation results illustrate the validity of the theoretical results.
基金supported in part by the National Laboratory of Radar Signal Processing Xidian Univrsity,Xi’an 710071,China。
文摘In distributed radar,most of existing radar networks operate in the tracking fusion mode which combines radar target tracks for a higher positioning accuracy.However,as the filtering covariance matrix indicating positioning accuracy often occupies many bits,the communication cost from local sensors to the fusion is not always sufficiently low for some wireless communication chan-nels.This paper studies how to compress data for distributed tracking fusion algorithms.Based on the K-singular value decomposition(K-SVD)algorithm,a sparse coding algorithm is presented to sparsely represent the filtering covariance matrix.Then the least square quantization(LSQ)algo-rithm is used to quantize the data according to the statistical characteristics of the sparse coeffi-cients.Quantized results are then coded with an arithmetic coding method which can further com-press data.Numerical results indicate that this tracking data compression algorithm drops the com-munication bandwidth to 4%at the cost of a 16%root mean squared error(RMSE)loss.
文摘Based on interpretations of the apatite fission track analysis data for 10 outcrop samples and forward modeling of confined fission track length distributions, the thermal history of rocks in the Shiwandashan basin and its adjacent area, southern China, has been qualitatively and semi quantitatively studied. The results reflect several features of the thermal history. Firstly, all the samples have experienced temperatures higher than 60-70 ℃. Secondly, the time that the basement strata (T 1 b ) on the northwestern side of the Shiwandashan basin were uplifted and exhumed to the unannealed upper crust (with a paleogeotemperature of below 60-70 ℃) is much earlier than the basement rocks ( γ 1 5) on the southeastern side of the basin. Thirdly, the thermal history of samples from the basin can be divided into six stages, i.e., the fast burial and heating stage (220-145 Ma), the transient cooling stage (145-135 Ma), the burial and heating stage (135-70 Ma), the rapid cooling stage (70-50 Ma), the relatively stable stage (50-20 Ma) and another rapid cooling stage (20 Ma to present).
基金supported in part by the National Key Research and Development Program of China under Grant 2022YFB3304800the National Natural Science Foundation of China under Grant U21A20475,61873050+1 种基金the Fundamental Research Funds for the Central Universities under Grant N2304007the Research Fund of State Key Laboratory of Synthetical Automation for Process Industries under Grant 2018ZCX14.
文摘The distributed tracking control problem for heterogeneous multi-agent systems with unknown system dynamics is investigated.The objective is to provide a data-driven distributed tracking control protocol that ensures tracking performance between agents and the leader.To this end,the concept of data informativity for matching conditions is introduced.Then,the data-based sufficient and necessary conditions to achieve state tracking are provided.Meanwhile,a data-driven parameterisation approach for designing the distributed tracking control protocol is given.Compared with previous results,the reference input is considered in the leader's dynamics,and the computational burden is reduced by solving a set of data-based equations and inequality constraints rather than iteration.Additionally,the developed results are still appropriate for handling the tracking control issue of the single linear system,and the current constraint that the reference system be stable is eased.Finally,two simulation examples are given to verify the proposed schemes'effectiveness.
文摘We propose a distributed labeled multi-Bernoulli(LMB)filter based on an efficient label matching method.Conventional distributed LMB filter fusion has the premise that the labels among local densities have already been matched.However,considering that the label space of each local posterior is independent,such a premise is not practical in many applications.To achieve distributed fusion practically,we propose an efficient label matching method derived from the divergence of arithmetic average(AA)mechanism,and subsequently label-wise LMB filter fusion is performed according to the matching results.Compared with existing label matching methods,this proposed method shows higher performance,especially in low detection probability scenarios.Moreover,to guarantee the consistency and completeness of the fusion outcome,the overall fusion procedure is designed into the following four stages:pre-fusion,label determination,posterior complement,and uniqueness check.The performance of the proposed label matching distributed LMB filter fusion is demonstrated in a challenging nonlinear bearings-only multi-target tracking(MTT)scenario.
基金supported in part by A*STARSERC Grant no.052 101 0037
文摘In the real world,centralized tracking in a large-scale wireless sensor network (WSN) may not be feasible due to the possible failure of fusion centre and the large communication delay in forwarding measurement data to the fusion centre. Distributed target tracking techniques can be employed by tasking sensor nodes near to the target to perform sensing,target state estimation and selection of future tasking sensor nodes. In this paper,the development and implementation of a prototype ultrasonic WSN test-bed to demonstrate distributed target tracking using the Extended Kalman Filter (EKF) algorithm is described. In the test-bed,a mobile robot is used to simulate the moving target,and static/mobile sensor nodes are deployed to detect and track the target. The sensor nodes and robots are equipped with sonar and MICAZ to receive and process instructions. Experimental evaluation of a number of sensor scheduling schemes are reported which shows the superior tracking performance of our distributed competition based sensor scheduling scheme.
基金support of the National Science Foundation(NSF)under Award Number:2115427 is gratefully acknowledged.SRS RN:Sustainable Transportation Electrification for an Equitable and Resilient Society(STEERS).
文摘Solar power is mostly influenced by solar irradiation,weather conditions,solar array mismatches and partial shading conditions.Therefore,before installing solar arrays,it is necessary to simulate and determine the possible power generated.Maximum power point tracking is needed in order to make sure that,at any time,the maximum power will be extracted from the photovoltaic system.However,maximum power point tracking is not a suitable solution for mismatches and partial shading conditions.To overcome the drawbacks of maximum power point tracking due to mismatches and shadows,distributed maximum power point tracking is util-ized in this paper.The solar farm can be distributed in different ways,including one DC-DC converter per group of modules or per module.In this paper,distributed maximum power point tracking per module is implemented,which has the highest efficiency.This technology is applied to electric vehicles(EVs)that can be charged with a Level 3 charging station in<1 hour.However,the problem is that charging an EV in<1 hour puts a lot of stress on the power grid,and there is not always enough peak power reserve in the existing power grid to charge EVs at that rate.Therefore,a Level 3(fast DC)EV charging station using a solar farm by implementing distributed maximum power point tracking is utilized to address this issue.Finally,the simulation result is reported using MATLAB®,LTSPICE and the System Advisor Model.Simulation results show that the proposed 1-MW solar system will provide 5 MWh of power each day,which is enough to fully charge~120 EVs each day.Additionally,the use of the proposed photovoltaic system benefits the environment by removing a huge amount of greenhouse gases and hazardous pollutants.For example,instead of supplying EVs with power from coal-fired power plants,1989 pounds of CO_(2) will be eliminated from the air per hour.
基金supported by the National Natural Science Foundation of China under Grant Nos.60934009, 60901037 and 61004138
文摘This paper considers the distributed Kalman filtering fusion with passive packet loss or initiative intermittent communications from local estimators to fusion center while the process noise does exist. When the local estimates are not lost too much, the authors propose an optimal distributed fusion algorithm which is equivalent to the corresponding centralized Kalman filtering fusion with complete communications even if the process noise does exist. When this condition is not satisfied, based on the above global optimality result and sensor data compression, the authors propose a suboptimal distributed fusion algorithm. Numerical examples show that this suboptimal algorithm still works well and significantly better than the standard distributed Kalman filtering fusion subject to packet loss even if the process noise power is quite large.
基金the National Science Foundation of China under Grant Nos.61973061and 61973064Hebei Natural Science Foundation for Distinguished Young Scholars under Grant Nos.F2019501043 and F2019501126。
文摘Progress in development of multi-agent control is reviewed.Different approaches for multiagent control,estimation,and optimization are discussed in a systematic way with particular emphasis on the graph-theoretic perspective.Attention is paid to the design of multi-agent systems via Laplacian dynamics,as well as the role of the graph Laplacian spectrum,the challenges of unbalanced digraphs,and consensus-based estimation of graph statistics.Some emergent issues,e.g.,distributed optimization,distributed average tracking,and distributed network games,are also reported,which have witnessed extensive development recently.There are over 200 references listed,mostly to recent contributions.
