In the constrained reentry trajectory design of hypersonic vehicles, multiple objectives with priorities bring about more difficulties to find the optimal solution. Therefore, a multi-objective reentry trajectory opti...In the constrained reentry trajectory design of hypersonic vehicles, multiple objectives with priorities bring about more difficulties to find the optimal solution. Therefore, a multi-objective reentry trajectory optimization (MORTO) approach via generalized varying domain (GVD) is proposed. Using the direct collocation approach, the trajectory optimization problem involving multiple objectives is discretized into a nonlinear multi-objective programming with priorities. In terms of fuzzy sets, the objectives are fuzzified into three types of fuzzy goals, and their constant tolerances are substituted by the varying domains. According to the principle that the objective with higher priority has higher satisfactory degree, the priority requirement is modeled as the order constraints of the varying domains. The corresponding two-side, single-side, and hybrid-side varying domain models are formulated for three fuzzy relations respectively. By regulating the parameter, the optimal reentry trajectory satisfying priorities can be achieved. Moreover, the performance about the parameter is analyzed, and the algorithm to find its specific value for maximum priority difference is proposed. The simulations demonstrate the effectiveness of the proposed method for hypersonic vehicles, and the comparisons with the traditional methods and sensitivity analysis are presented.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously a...This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.展开更多
针对未来战争对无人系统的需求不断增加,提出一种适用于狭小空间和复杂环境的新型无人系统——两栖无人作战车系统,同时具备地面行驶、墙面爬行、空中飞行和协同作战能力。采用基于Agent的建模与仿真(agent-based modeling and simulati...针对未来战争对无人系统的需求不断增加,提出一种适用于狭小空间和复杂环境的新型无人系统——两栖无人作战车系统,同时具备地面行驶、墙面爬行、空中飞行和协同作战能力。采用基于Agent的建模与仿真(agent-based modeling and simulation,ABMS)方法,在分析其应用任务场景的基础上,通过构造任务场景、桌面模型、仿真验证,深入分析两栖无人作战车系统应具备的功能,并根据分析结果提出所需解决的关键技术。结果表明:该系统对扩展无人系统任务环境、提升自主作战能力有着重要意义。展开更多
土地生态安全是土地资源持续利用的核心,由人类活动造成的土地利用变化改变生态系统结构与功能,对区域生态安全系统产生严重影响。为探究近年来重庆市及2030年生态安全变化情况,以重庆市为研究对象,采用PLUS(patch-level land use simul...土地生态安全是土地资源持续利用的核心,由人类活动造成的土地利用变化改变生态系统结构与功能,对区域生态安全系统产生严重影响。为探究近年来重庆市及2030年生态安全变化情况,以重庆市为研究对象,采用PLUS(patch-level land use simulation)模型模拟2030年自然发展、生态优先、发展优先情景下土地利用变化。基于生态学角度构建生态安全评价指标体系,并结合突变模型定量评价土地生态安全水平。结果表明重庆市土地利用类型空间分布差异较大,耕地面积减少3 995.14 km^(2),建设用地面积增加1 147.36 km^(2),实现城市快速发展;2000—2020年重庆市生态安全处于一般安全等级以上面积占比呈增加-降低-增加-减少趋势,总体呈上升趋势。同时三种情景下处于在相对安全及以上占64.53%、67.31%、55.97%;重庆市生态安全空间格局与人口密度、GDP等空间格局相反,与植被覆盖、坡度等自然数据空间格局相符。通过对往年及不同情景下的土地利用变化情况进行生态评定,为生态及经济高质量协同发展提供依据。展开更多
综合能源系统(integrated energy system,IES)内存在的多种不确定性因素,使得系统实际规划与运行面临各种风险,给系统安全、稳定、经济运行带来了诸多不利影响。如何削弱或消除不确定因素对综合能源系统的影响,是综合能源系统领域的重...综合能源系统(integrated energy system,IES)内存在的多种不确定性因素,使得系统实际规划与运行面临各种风险,给系统安全、稳定、经济运行带来了诸多不利影响。如何削弱或消除不确定因素对综合能源系统的影响,是综合能源系统领域的重要研究内容之一。首先,本文对综合能源系统中分布式能源、负荷、交通以及能源价格等多种不确定性因素产生机理进行分析,并研究其对综合能源系统的影响;其次,重点对场景法、点估计法、区间分析法、模糊分析法以及不确定集等多种不确定性分析方法进行介绍,并详细阐述这些方法在综合能源系统能源预测、负荷预测、潮流计算、能源市场、系统规划、经济调度以及稳定控制等领域的研究情况。最后,对未来综合能源系统不确定性研究中需要关注的问题进行了展望,以期为综合能源系统不确定性研究提供参考。展开更多
To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on ext...To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on extremum response surface method(ERSM).Firstly,the basic theories of the ERSM and DCERSM were investigated,and the strengths of DCERSM were proved theoretically.Secondly,the mathematical model of the DCERSM was established based upon extremum response surface function(ERSF).Finally,this model was applied to the reliability analysis of blade-tip radial running clearance(BTRRC)of an aeroengine high pressure turbine(HPT)to verify its advantages.The results show that the DCERSM can not only reshape the possibility of the reliability analysis for the complex turbo machinery,but also greatly improve the computational speed,save the computational time and improve the computational efficiency while keeping the accuracy.Thus,the DCERSM is verified to be feasible and effective in the dynamic assembly reliability(DAR)analysis of complex machinery.Moreover,this method offers an useful insight for designing and optimizing the dynamic reliability of complex machinery.展开更多
基金supported by the Natural Science Foundation of Tianjin(12JCZDJC30300)the Research Foundation of Tianjin Key Laboratory of Process Measurement and Control(TKLPMC-201613)the State Scholarship Fund of China
文摘In the constrained reentry trajectory design of hypersonic vehicles, multiple objectives with priorities bring about more difficulties to find the optimal solution. Therefore, a multi-objective reentry trajectory optimization (MORTO) approach via generalized varying domain (GVD) is proposed. Using the direct collocation approach, the trajectory optimization problem involving multiple objectives is discretized into a nonlinear multi-objective programming with priorities. In terms of fuzzy sets, the objectives are fuzzified into three types of fuzzy goals, and their constant tolerances are substituted by the varying domains. According to the principle that the objective with higher priority has higher satisfactory degree, the priority requirement is modeled as the order constraints of the varying domains. The corresponding two-side, single-side, and hybrid-side varying domain models are formulated for three fuzzy relations respectively. By regulating the parameter, the optimal reentry trajectory satisfying priorities can be achieved. Moreover, the performance about the parameter is analyzed, and the algorithm to find its specific value for maximum priority difference is proposed. The simulations demonstrate the effectiveness of the proposed method for hypersonic vehicles, and the comparisons with the traditional methods and sensitivity analysis are presented.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
文摘This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.
文摘针对未来战争对无人系统的需求不断增加,提出一种适用于狭小空间和复杂环境的新型无人系统——两栖无人作战车系统,同时具备地面行驶、墙面爬行、空中飞行和协同作战能力。采用基于Agent的建模与仿真(agent-based modeling and simulation,ABMS)方法,在分析其应用任务场景的基础上,通过构造任务场景、桌面模型、仿真验证,深入分析两栖无人作战车系统应具备的功能,并根据分析结果提出所需解决的关键技术。结果表明:该系统对扩展无人系统任务环境、提升自主作战能力有着重要意义。
文摘土地生态安全是土地资源持续利用的核心,由人类活动造成的土地利用变化改变生态系统结构与功能,对区域生态安全系统产生严重影响。为探究近年来重庆市及2030年生态安全变化情况,以重庆市为研究对象,采用PLUS(patch-level land use simulation)模型模拟2030年自然发展、生态优先、发展优先情景下土地利用变化。基于生态学角度构建生态安全评价指标体系,并结合突变模型定量评价土地生态安全水平。结果表明重庆市土地利用类型空间分布差异较大,耕地面积减少3 995.14 km^(2),建设用地面积增加1 147.36 km^(2),实现城市快速发展;2000—2020年重庆市生态安全处于一般安全等级以上面积占比呈增加-降低-增加-减少趋势,总体呈上升趋势。同时三种情景下处于在相对安全及以上占64.53%、67.31%、55.97%;重庆市生态安全空间格局与人口密度、GDP等空间格局相反,与植被覆盖、坡度等自然数据空间格局相符。通过对往年及不同情景下的土地利用变化情况进行生态评定,为生态及经济高质量协同发展提供依据。
文摘综合能源系统(integrated energy system,IES)内存在的多种不确定性因素,使得系统实际规划与运行面临各种风险,给系统安全、稳定、经济运行带来了诸多不利影响。如何削弱或消除不确定因素对综合能源系统的影响,是综合能源系统领域的重要研究内容之一。首先,本文对综合能源系统中分布式能源、负荷、交通以及能源价格等多种不确定性因素产生机理进行分析,并研究其对综合能源系统的影响;其次,重点对场景法、点估计法、区间分析法、模糊分析法以及不确定集等多种不确定性分析方法进行介绍,并详细阐述这些方法在综合能源系统能源预测、负荷预测、潮流计算、能源市场、系统规划、经济调度以及稳定控制等领域的研究情况。最后,对未来综合能源系统不确定性研究中需要关注的问题进行了展望,以期为综合能源系统不确定性研究提供参考。
基金Project(51175017)supported by the National Natural Science Foundation of ChinaProject(YWF-12-RBYJ-008)supported by the Innovation Foundation of Beihang University for PhD Graduates,ChinaProject(20111102110011)supported by the Research Fund for the Doctoral Program of Higher Education of China
文摘To make the dynamic assembly reliability analysis more effective for complex machinery of multi-object multi-discipline(MOMD),distributed collaborative extremum response surface method(DCERSM)was proposed based on extremum response surface method(ERSM).Firstly,the basic theories of the ERSM and DCERSM were investigated,and the strengths of DCERSM were proved theoretically.Secondly,the mathematical model of the DCERSM was established based upon extremum response surface function(ERSF).Finally,this model was applied to the reliability analysis of blade-tip radial running clearance(BTRRC)of an aeroengine high pressure turbine(HPT)to verify its advantages.The results show that the DCERSM can not only reshape the possibility of the reliability analysis for the complex turbo machinery,but also greatly improve the computational speed,save the computational time and improve the computational efficiency while keeping the accuracy.Thus,the DCERSM is verified to be feasible and effective in the dynamic assembly reliability(DAR)analysis of complex machinery.Moreover,this method offers an useful insight for designing and optimizing the dynamic reliability of complex machinery.
