针对大规模卫星高精度编队控制问题,提出了一种基于吸引法则的深度确定性策略梯度控制方法(attraction-based deep deterministic policy gradient,ADDPG)。首先阐述了超立方体拓扑编队拓扑构型特性,建立了卫星编队动力学模型,设计了超...针对大规模卫星高精度编队控制问题,提出了一种基于吸引法则的深度确定性策略梯度控制方法(attraction-based deep deterministic policy gradient,ADDPG)。首先阐述了超立方体拓扑编队拓扑构型特性,建立了卫星编队动力学模型,设计了超立方体卫星编队虚拟中心用于衡量编队整体飞行状态。为解决无模型深度强化学习的探索和扩展平衡问题,设计了ε-imitation动作选择策略方法,最终提出了基于ADDPG的卫星编队控制策略。算法不依赖于环境模型,通过充分利用已有信息,可以降低学习模型初期探索过程中的盲目试错。仿真结果表明ADDPG策略以较少的能量消耗达到更高的精度,相比知名算法在加快编队收敛速度的同时,误差减少5%以上,能量消耗减少7%以上,验证了算法的有效性。展开更多
Generalized hypercubes (denoted by Q(d1,d2,... ,dn)) is an important network topology for parallel processing computer systems. Some methods of forming big cycle from small cycles and links have been developed. Ba...Generalized hypercubes (denoted by Q(d1,d2,... ,dn)) is an important network topology for parallel processing computer systems. Some methods of forming big cycle from small cycles and links have been developed. Basing on which, we has proved that in generalized hypercubes, every edge can be contained on a cycle of every length from 3 to IV(G)I inclusive and all kinds of length cycles have been constructed. The edgepanciclieity and node-pancilicity of generalized hypercubes can be applied in the topology design of computer networks to improve the network performance.展开更多
文摘针对大规模卫星高精度编队控制问题,提出了一种基于吸引法则的深度确定性策略梯度控制方法(attraction-based deep deterministic policy gradient,ADDPG)。首先阐述了超立方体拓扑编队拓扑构型特性,建立了卫星编队动力学模型,设计了超立方体卫星编队虚拟中心用于衡量编队整体飞行状态。为解决无模型深度强化学习的探索和扩展平衡问题,设计了ε-imitation动作选择策略方法,最终提出了基于ADDPG的卫星编队控制策略。算法不依赖于环境模型,通过充分利用已有信息,可以降低学习模型初期探索过程中的盲目试错。仿真结果表明ADDPG策略以较少的能量消耗达到更高的精度,相比知名算法在加快编队收敛速度的同时,误差减少5%以上,能量消耗减少7%以上,验证了算法的有效性。
基金This project is supported by National Natural Science Foundation of China (10671081)
文摘Generalized hypercubes (denoted by Q(d1,d2,... ,dn)) is an important network topology for parallel processing computer systems. Some methods of forming big cycle from small cycles and links have been developed. Basing on which, we has proved that in generalized hypercubes, every edge can be contained on a cycle of every length from 3 to IV(G)I inclusive and all kinds of length cycles have been constructed. The edgepanciclieity and node-pancilicity of generalized hypercubes can be applied in the topology design of computer networks to improve the network performance.