This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning(DISOMP)algorithm for multiple Unmanned Aerial...This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning(DISOMP)algorithm for multiple Unmanned Aerial Vehicles(multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization(ACO) algorithm, an attack module designed based on the Parallel Approach(PA)scheme, a threat avoidance module designed based on the Dubins Curve(DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.展开更多
Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical ...Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.展开更多
This paper proposes an improved optimal operation planning method for residential PEFC-CGS (Polymer Electrolyte Fuel CellCo-Generation System). Residential PEFC-CGS has recently been gathering attention as one of the ...This paper proposes an improved optimal operation planning method for residential PEFC-CGS (Polymer Electrolyte Fuel CellCo-Generation System). Residential PEFC-CGS has recently been gathering attention as one of the distributed power sources with high efficiency and low environmental impacts. Previous research pointed out that the output variations of PEFC adversely affect the durability. It can be surmised that smaller output variations will be desired to extend durability years. However, in this field, ramping rate have not been sufficiently considered. For local search and tabu search, ramping rate constraint makes our operation planning difficult because it restricts the search for feasible neighborhood solutions. Therefore, the authors proposed a method to deal with typical and harsher ramping rate constraints in comparison with conventional methods. There are two key points for the improvement. One is the reinforcement of the search along the output power axis;the other is to make use of the strategy of tabu search which avoids the local optimal solutions. The simulation results show the effectiveness of the proposed method in the daily operation planning. Furthermore, in the case using typical ramping rate parameter, it is confirmed that tabu search doesn’t contribute the reduction of daily operational cost due to the above stated restriction of the search area.展开更多
为解决低轨遥感星座协同任务规划面临的计算复杂度高、通信开销大、动态响应能力弱等问题,提出一种基于任务聚类与禁忌搜索的改进合同网算法(improved contract net protocol based on task clustering and tabu search,CN-TCTS).该算...为解决低轨遥感星座协同任务规划面临的计算复杂度高、通信开销大、动态响应能力弱等问题,提出一种基于任务聚类与禁忌搜索的改进合同网算法(improved contract net protocol based on task clustering and tabu search,CN-TCTS).该算法采用“单星调度-全局分配”的分层求解框架.首先,通过任务聚类合并元任务,有效缩减解空间;其次,设计了动态约束禁忌搜索算法(dynamic constraint tabu search,DCTS),通过价值导向的邻域搜索策略实现单星任务序列的快速规划;最后,在全局分配阶段,引入多种策略对传统合同网协议进行改进,实现任务的高效分配与冲突消解.仿真结果表明,本文所提CN-TCTS算法在400个任务的大规模场景下,任务完成率仍保持82.0%,且平均通信轮次仅为6.6轮.此外,在卫星突发失效的动态场景下,该算法表现出更强的鲁棒性,收益损失率更低.此外,局部规划算法仿真中验证了DCTS算法在收敛速度与解质量方面的优势.展开更多
A target is assumed to move according to a Brownian motion on the real line. The searcher starts from the origin and moves in the two directions from the starting point. The object is to detect the target. The purpose...A target is assumed to move according to a Brownian motion on the real line. The searcher starts from the origin and moves in the two directions from the starting point. The object is to detect the target. The purpose of this paper is to find the conditions under which the expected value of the first meeting time of the searcher and the target is finite, and to show the existence of a search plan which made this expected value minimum.展开更多
自重构波状爬行(self-reconfiguration wave-like crawling,SWC)机器人具有特殊的串/并联连接状态,其在运动规划过程中更需要生成连续可行的轨迹。传统运动规划算法存在效率低下、生成路径不符合运动学约束的问题。本文提出了一种改进...自重构波状爬行(self-reconfiguration wave-like crawling,SWC)机器人具有特殊的串/并联连接状态,其在运动规划过程中更需要生成连续可行的轨迹。传统运动规划算法存在效率低下、生成路径不符合运动学约束的问题。本文提出了一种改进的信息增强快速探索随机树运动规划方法。首先以RRT-Connect(rapidly-exploring random tree connect)算法为基础,生成初始可行路径,构建椭圆状态空间采样域,实现随机树的快速生长。其次,基于最小化的加加速度目标函数和Hessian矩阵优化多项式轨迹,生成符合SWC机器人运动学特性的平滑轨迹。最后,基于不同的障碍物场景进行路径规划仿真,以验证优化后算法的效果。仿真结果表明,相较于传统算法,所提方法在多种障碍物环境中可显著提升路径规划效率,缩短全局采样时间和规划路径长度,并可有效地避免SWC机器人运动过程中的急加速转弯,消除路径中的尖锐转折,更符合实际作业需求。展开更多
基金supported in part by National Natural Science Foundation of China (Nos. 61741313, 61673209, and 61533008)Jiangsu Six Peak of Talents Program, China (No. KTHY-027)Postgraduate Research & Practice Innovation Program of Jiangsu Province, China (No. KYCX18_0303)
文摘This article studies the cooperative search-attack mission problem with dynamic targets and threats, and presents a Distributed Intelligent Self-Organized Mission Planning(DISOMP)algorithm for multiple Unmanned Aerial Vehicles(multi-UAV). The DISOMP algorithm can be divided into four modules: a search module designed based on the distributed Ant Colony Optimization(ACO) algorithm, an attack module designed based on the Parallel Approach(PA)scheme, a threat avoidance module designed based on the Dubins Curve(DC) and a communication module designed for information exchange among the multi-UAV system and the dynamic environment. A series of simulations of multi-UAV searching and attacking the moving targets are carried out, in which the search-attack mission completeness, execution efficiency and system suitability of the DISOMP algorithm are analyzed. The simulation results exhibit that the DISOMP algorithm based on online distributed down-top strategy is characterized by good flexibility, scalability and adaptability, in the dynamic targets searching and attacking problem.
文摘Aiming at the practical application of Unmanned Underwater Vehicle(UUV)in underwater combat,this paper proposes a battlefield ambush scene with UUV considering ocean current.Firstly,by establishing these mathematical models of ocean current environment,target movement,and sonar detection,the probability calculation methods of single UUV searching target and multiple UUV cooperatively searching target are given respectively.Then,based on the Hybrid Quantum-behaved Particle Swarm Optimization(HQPSO)algorithm,the path with the highest target search probability is found.Finally,through simulation calculations,the influence of different UUV parameters and target parameters on the target search probability is analyzed,and the minimum number of UUVs that need to be deployed to complete the ambush task is demonstrated,and the optimal search path scheme is obtained.The method proposed in this paper provides a theoretical basis for the practical application of UUV in the future combat.
文摘This paper proposes an improved optimal operation planning method for residential PEFC-CGS (Polymer Electrolyte Fuel CellCo-Generation System). Residential PEFC-CGS has recently been gathering attention as one of the distributed power sources with high efficiency and low environmental impacts. Previous research pointed out that the output variations of PEFC adversely affect the durability. It can be surmised that smaller output variations will be desired to extend durability years. However, in this field, ramping rate have not been sufficiently considered. For local search and tabu search, ramping rate constraint makes our operation planning difficult because it restricts the search for feasible neighborhood solutions. Therefore, the authors proposed a method to deal with typical and harsher ramping rate constraints in comparison with conventional methods. There are two key points for the improvement. One is the reinforcement of the search along the output power axis;the other is to make use of the strategy of tabu search which avoids the local optimal solutions. The simulation results show the effectiveness of the proposed method in the daily operation planning. Furthermore, in the case using typical ramping rate parameter, it is confirmed that tabu search doesn’t contribute the reduction of daily operational cost due to the above stated restriction of the search area.
文摘为解决低轨遥感星座协同任务规划面临的计算复杂度高、通信开销大、动态响应能力弱等问题,提出一种基于任务聚类与禁忌搜索的改进合同网算法(improved contract net protocol based on task clustering and tabu search,CN-TCTS).该算法采用“单星调度-全局分配”的分层求解框架.首先,通过任务聚类合并元任务,有效缩减解空间;其次,设计了动态约束禁忌搜索算法(dynamic constraint tabu search,DCTS),通过价值导向的邻域搜索策略实现单星任务序列的快速规划;最后,在全局分配阶段,引入多种策略对传统合同网协议进行改进,实现任务的高效分配与冲突消解.仿真结果表明,本文所提CN-TCTS算法在400个任务的大规模场景下,任务完成率仍保持82.0%,且平均通信轮次仅为6.6轮.此外,在卫星突发失效的动态场景下,该算法表现出更强的鲁棒性,收益损失率更低.此外,局部规划算法仿真中验证了DCTS算法在收敛速度与解质量方面的优势.
文摘A target is assumed to move according to a Brownian motion on the real line. The searcher starts from the origin and moves in the two directions from the starting point. The object is to detect the target. The purpose of this paper is to find the conditions under which the expected value of the first meeting time of the searcher and the target is finite, and to show the existence of a search plan which made this expected value minimum.
文摘自重构波状爬行(self-reconfiguration wave-like crawling,SWC)机器人具有特殊的串/并联连接状态,其在运动规划过程中更需要生成连续可行的轨迹。传统运动规划算法存在效率低下、生成路径不符合运动学约束的问题。本文提出了一种改进的信息增强快速探索随机树运动规划方法。首先以RRT-Connect(rapidly-exploring random tree connect)算法为基础,生成初始可行路径,构建椭圆状态空间采样域,实现随机树的快速生长。其次,基于最小化的加加速度目标函数和Hessian矩阵优化多项式轨迹,生成符合SWC机器人运动学特性的平滑轨迹。最后,基于不同的障碍物场景进行路径规划仿真,以验证优化后算法的效果。仿真结果表明,相较于传统算法,所提方法在多种障碍物环境中可显著提升路径规划效率,缩短全局采样时间和规划路径长度,并可有效地避免SWC机器人运动过程中的急加速转弯,消除路径中的尖锐转折,更符合实际作业需求。
