The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is...The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is extended to some extent, and accordingly, the results of global ultimate boundedness for stochastic nonlinear systems are developed. Next, a new design scheme of fuzzy adaptive control is proposed. The advantage of it is that it does not require priori knowledge of virtual control gain function sign, which is usually demanded in many designs. At the same time, the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound. By theoretical analysis, the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.展开更多
With the continuous development of network func-tions virtualization(NFV)and software-defined networking(SDN)technologies and the explosive growth of network traffic,the requirement for computing resources in the netw...With the continuous development of network func-tions virtualization(NFV)and software-defined networking(SDN)technologies and the explosive growth of network traffic,the requirement for computing resources in the network has risen sharply.Due to the high cost of edge computing resources,coordinating the cloud and edge computing resources to improve the utilization efficiency of edge computing resources is still a considerable challenge.In this paper,we focus on optimiz-ing the placement of network services in cloud-edge environ-ments to maximize the efficiency.It is first proved that,in cloud-edge environments,placing one service function chain(SFC)integrally in the cloud or at the edge can improve the utilization efficiency of edge resources.Then a virtual network function(VNF)performance-resource(P-R)function is proposed to repre-sent the relationship between the VNF instance computing per-formance and the allocated computing resource.To select the SFCs that are most suitable to deploy at the edge,a VNF place-ment and resource allocation model is built to configure each VNF with its particular P-R function.Moreover,a heuristic recur-sive algorithm is designed called the recursive algorithm for max edge throughput(RMET)to solve the model.Through simula-tions on two scenarios,it is verified that RMET can improve the utilization efficiency of edge computing resources.展开更多
针对如何在部署服务功能链SFC(service function chain)的同时兼顾低能耗与网络负载均衡,提出了一种以节点负载状态预测为基础的SFC部署方法NIR-IACA(improved ant colony algorithm based on node importance ranking)。首先,使用基于...针对如何在部署服务功能链SFC(service function chain)的同时兼顾低能耗与网络负载均衡,提出了一种以节点负载状态预测为基础的SFC部署方法NIR-IACA(improved ant colony algorithm based on node importance ranking)。首先,使用基于粒子群优化的CNN-GRU模型(particle swarm optimization-based CNN-GRU model,PCNN-GRU),结合广义网络温度(GNT)预测网络节点的负载状态,并据此为SFC部署提供备选节点;其次,基于最短路径优先策略的改进蚁群算法(ant colony algorithm,ACA)设计SFC部署节点选择策略(high availability and resource scheduling,HARS)且对选定节点进行虚拟链路映射,优化目标兼顾基础设施网络低能耗与负载均衡的要求。基于Clearwater VNF公开数据集的实验结果表明,提出的NIR-IACA方法与现有的MC-EEVP算法、DPVC算法以及RQAP算法相比平均节省13.09%的能耗,并提高12.98%的负载均衡能力,且在维持相对较高SFC请求的接受率的同时,可以较好地实现SFC部署的能耗与负载均衡联合优化。展开更多
服务功能链(Service Function Chain, SFC)部署是实现网络服务灵活多样的关键技术,SFC可靠性是SFC部署工作中的重要指标。现有方法在提高SFC可靠性的同时造成了网络资源的浪费。为了平衡SFC可靠性和网络资源消耗,设计了一种VNF分集式备...服务功能链(Service Function Chain, SFC)部署是实现网络服务灵活多样的关键技术,SFC可靠性是SFC部署工作中的重要指标。现有方法在提高SFC可靠性的同时造成了网络资源的浪费。为了平衡SFC可靠性和网络资源消耗,设计了一种VNF分集式备份(VNF Diversity Backup, VDB)机制,利用有限的网络资源改良SFC,将低可靠VNF实例拆分为两个副本实例,并对VNF副本实例进行交叉备份。在SFC部署阶段,提出了一种基于VDB机制的服务功能链部署方法,根据VDB机制的改良结果及网络拓扑属性构建多阶段图,采用基于Viterbi的动态规划算法在多阶段图中搜索最优部署路径。此外,引入评价指标备份性价比来衡量SFC可靠性和网络资源消耗的平衡效果。仿真结果表明,所提方法有效地平衡了可靠性和网络资源消耗,并且优化了传输时延。展开更多
目的探索虚拟现实(VR)技术在脑卒中领域应用的研究现状和前沿热点。方法 检索Web of Science核心合集2014年1月至2024年8月VR技术应用于脑卒中领域的文献,借助文献计量学软件对发文作者、机构、关键词等绘制可视化的知识图谱。结果 剔...目的探索虚拟现实(VR)技术在脑卒中领域应用的研究现状和前沿热点。方法 检索Web of Science核心合集2014年1月至2024年8月VR技术应用于脑卒中领域的文献,借助文献计量学软件对发文作者、机构、关键词等绘制可视化的知识图谱。结果 剔除校稿通知、编辑资料、会议论文等,共纳入文献785篇。近10年来,全球该研究领域新增发文量呈上升趋势,中国是发文量最多的国家(130篇),发文量最多的作者是Lamontagne Anouk(10篇)和Calabro Rocco Salvatore(10篇),发文量最多的机构和期刊分别是麦吉尔大学(加拿大,27篇)和Journal of Neuroengineering and Rehabilitation(60篇)。关键词分析和最强突发关键词表明研究热点聚焦在上肢、步态训练、运动功能、认知康复、单侧忽视、刺激、运动想象、大脑皮质重组等。结论 近10年,VR技术在脑卒中领域应用的广度、深度逐步增加,给脑卒中康复带来了新的机遇和思考。VR技术与神经调节、神经成像、脑机接口、人工智能、远程医疗相结合的新形态可能是未来的研究热点和方向。展开更多
新型脉冲功率设备对直流侧母线电压提出较高的性能要求,为减小脉冲负载对直流电压波动率的影响,建立带脉冲负载三相整流器拓扑结构及数学模型,并在现有无源控制(passivity based control,PBC)设计的基础上,以保证系统稳定性为前提,提出...新型脉冲功率设备对直流侧母线电压提出较高的性能要求,为减小脉冲负载对直流电压波动率的影响,建立带脉冲负载三相整流器拓扑结构及数学模型,并在现有无源控制(passivity based control,PBC)设计的基础上,以保证系统稳定性为前提,提出注入虚拟储能的无源控制算法(virtual energy storage injection PBC,VESI-PBC),该算法以提高能量函数收敛速度为目标,可有效降低直流母线电压波动率,提高抗负载扰动能力。分别基于根轨迹法和时域分析法,讨论VESI-PBC引入储能矩阵后,增大虚拟电感值L_(n)对系统的稳定性和动态性能的影响。为满足直流侧性能要求和保证系统稳定性,利用脉冲负载对直流电压波动率的影响规律,提出L_(n)自适应选取函数f(f_(PL)),使L_(n)自适应平衡系统高频毛刺和低频强脉冲冲击的不同需求。最后,通过仿真及实际试验,验证VESI-PBC算法对减小直流母线电压波动率的有效性,并指出该算法的实质是控制内环电流超前响应直流电压的动态变化及其变化趋势,由此具有较强的抗负载扰动能力,适用于负载脉冲功率等级高、动态特性强烈的场合。展开更多
大规模虚拟电厂(virtual power plant,VPP)逐步具备与传统发电资源对等的地位,其优化运行策略将显著影响电力市场的均衡状态。高效表征虚拟电厂在关键端口下的外特性将促进虚拟电厂与现有市场模式的有效兼容,对于其深度参与电力市场具...大规模虚拟电厂(virtual power plant,VPP)逐步具备与传统发电资源对等的地位,其优化运行策略将显著影响电力市场的均衡状态。高效表征虚拟电厂在关键端口下的外特性将促进虚拟电厂与现有市场模式的有效兼容,对于其深度参与电力市场具有十分重要的现实意义。基于改进多参数线性规划(multi-parametric linear programming,MPLP)理论提出虚拟电厂边际成本函数解析表征方法,通过虚拟电厂与主网在公共连接点(point of common coupling,PCC)处的交易电量这一低维参数,反映其整体灵活性、交易可行域及边际成本。基于成本最小化将初始参数空间优化分割为若干临界域(critical region,CR),随后,揭示优化分割的经济学特性,并利用该特性刻画参数空间与虚拟电厂成本的分段映射关系。最后,基于改进的IEEE 33及IEEE 123节点系统验证所提算法的有效性,为虚拟电厂以非迭代的方式参与市场出清提供理论基础。展开更多
基金Supported by National Natural Science Foundation of P. R. China (60572070, 60325311, 60534010) Natural Science Foundation of Liaoning Province (20022030)
文摘The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is extended to some extent, and accordingly, the results of global ultimate boundedness for stochastic nonlinear systems are developed. Next, a new design scheme of fuzzy adaptive control is proposed. The advantage of it is that it does not require priori knowledge of virtual control gain function sign, which is usually demanded in many designs. At the same time, the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound. By theoretical analysis, the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.
基金This work was supported by the Key Research and Development(R&D)Plan of Heilongjiang Province of China(JD22A001).
文摘With the continuous development of network func-tions virtualization(NFV)and software-defined networking(SDN)technologies and the explosive growth of network traffic,the requirement for computing resources in the network has risen sharply.Due to the high cost of edge computing resources,coordinating the cloud and edge computing resources to improve the utilization efficiency of edge computing resources is still a considerable challenge.In this paper,we focus on optimiz-ing the placement of network services in cloud-edge environ-ments to maximize the efficiency.It is first proved that,in cloud-edge environments,placing one service function chain(SFC)integrally in the cloud or at the edge can improve the utilization efficiency of edge resources.Then a virtual network function(VNF)performance-resource(P-R)function is proposed to repre-sent the relationship between the VNF instance computing per-formance and the allocated computing resource.To select the SFCs that are most suitable to deploy at the edge,a VNF place-ment and resource allocation model is built to configure each VNF with its particular P-R function.Moreover,a heuristic recur-sive algorithm is designed called the recursive algorithm for max edge throughput(RMET)to solve the model.Through simula-tions on two scenarios,it is verified that RMET can improve the utilization efficiency of edge computing resources.
文摘针对如何在部署服务功能链SFC(service function chain)的同时兼顾低能耗与网络负载均衡,提出了一种以节点负载状态预测为基础的SFC部署方法NIR-IACA(improved ant colony algorithm based on node importance ranking)。首先,使用基于粒子群优化的CNN-GRU模型(particle swarm optimization-based CNN-GRU model,PCNN-GRU),结合广义网络温度(GNT)预测网络节点的负载状态,并据此为SFC部署提供备选节点;其次,基于最短路径优先策略的改进蚁群算法(ant colony algorithm,ACA)设计SFC部署节点选择策略(high availability and resource scheduling,HARS)且对选定节点进行虚拟链路映射,优化目标兼顾基础设施网络低能耗与负载均衡的要求。基于Clearwater VNF公开数据集的实验结果表明,提出的NIR-IACA方法与现有的MC-EEVP算法、DPVC算法以及RQAP算法相比平均节省13.09%的能耗,并提高12.98%的负载均衡能力,且在维持相对较高SFC请求的接受率的同时,可以较好地实现SFC部署的能耗与负载均衡联合优化。
文摘目的探索虚拟现实(VR)技术在脑卒中领域应用的研究现状和前沿热点。方法 检索Web of Science核心合集2014年1月至2024年8月VR技术应用于脑卒中领域的文献,借助文献计量学软件对发文作者、机构、关键词等绘制可视化的知识图谱。结果 剔除校稿通知、编辑资料、会议论文等,共纳入文献785篇。近10年来,全球该研究领域新增发文量呈上升趋势,中国是发文量最多的国家(130篇),发文量最多的作者是Lamontagne Anouk(10篇)和Calabro Rocco Salvatore(10篇),发文量最多的机构和期刊分别是麦吉尔大学(加拿大,27篇)和Journal of Neuroengineering and Rehabilitation(60篇)。关键词分析和最强突发关键词表明研究热点聚焦在上肢、步态训练、运动功能、认知康复、单侧忽视、刺激、运动想象、大脑皮质重组等。结论 近10年,VR技术在脑卒中领域应用的广度、深度逐步增加,给脑卒中康复带来了新的机遇和思考。VR技术与神经调节、神经成像、脑机接口、人工智能、远程医疗相结合的新形态可能是未来的研究热点和方向。
文摘新型脉冲功率设备对直流侧母线电压提出较高的性能要求,为减小脉冲负载对直流电压波动率的影响,建立带脉冲负载三相整流器拓扑结构及数学模型,并在现有无源控制(passivity based control,PBC)设计的基础上,以保证系统稳定性为前提,提出注入虚拟储能的无源控制算法(virtual energy storage injection PBC,VESI-PBC),该算法以提高能量函数收敛速度为目标,可有效降低直流母线电压波动率,提高抗负载扰动能力。分别基于根轨迹法和时域分析法,讨论VESI-PBC引入储能矩阵后,增大虚拟电感值L_(n)对系统的稳定性和动态性能的影响。为满足直流侧性能要求和保证系统稳定性,利用脉冲负载对直流电压波动率的影响规律,提出L_(n)自适应选取函数f(f_(PL)),使L_(n)自适应平衡系统高频毛刺和低频强脉冲冲击的不同需求。最后,通过仿真及实际试验,验证VESI-PBC算法对减小直流母线电压波动率的有效性,并指出该算法的实质是控制内环电流超前响应直流电压的动态变化及其变化趋势,由此具有较强的抗负载扰动能力,适用于负载脉冲功率等级高、动态特性强烈的场合。
文摘大规模虚拟电厂(virtual power plant,VPP)逐步具备与传统发电资源对等的地位,其优化运行策略将显著影响电力市场的均衡状态。高效表征虚拟电厂在关键端口下的外特性将促进虚拟电厂与现有市场模式的有效兼容,对于其深度参与电力市场具有十分重要的现实意义。基于改进多参数线性规划(multi-parametric linear programming,MPLP)理论提出虚拟电厂边际成本函数解析表征方法,通过虚拟电厂与主网在公共连接点(point of common coupling,PCC)处的交易电量这一低维参数,反映其整体灵活性、交易可行域及边际成本。基于成本最小化将初始参数空间优化分割为若干临界域(critical region,CR),随后,揭示优化分割的经济学特性,并利用该特性刻画参数空间与虚拟电厂成本的分段映射关系。最后,基于改进的IEEE 33及IEEE 123节点系统验证所提算法的有效性,为虚拟电厂以非迭代的方式参与市场出清提供理论基础。
