Formation control problem is one of the most concerned topics within the realm of swarm intelligence, which is usually solved by conventional mathematical approaches. In this paper, however, we presents a metaheuristic approach that leverages a natural co-evolutionary strategy to solve the formation control problem for a swarm of missiles. The missile swarm is modeled by a second-order system with heterogeneous reference target, and exponential error function is made to be the objective function such that the swarm converge to optimal equilibrium states satisfying certain formation requirements. Focusing on the issue of local optimum and unstable evolution, we incorporate a novel model-based policy constraint and a population adaptation strategies that greatly alleviates the performance degradation. With application of the Molloy-Reed criterion in the field of network communication, we developed an adaptive topology method that assure the connectivity under node failure and its effectiveness are validated both theoretically and experimentally. Experimental results valid the effectiveness of the proposed formation control approach. More significantly, we showed that it is feasible to treat generic formation control problem as Markov Decision Process(MDP) and solve it through iterative learning.
翻译:形成控制问题是群集情报领域最关注的议题之一,通常通过常规数学方法解决。然而,在本文件中,我们提出一种美术方法,利用自然共同进化战略解决成群导弹的形成控制问题。导弹群由二阶系统模拟,其参照目标各异,指数误差函数被确定为客观功能,使群集集中到最佳平衡状态的国家满足了某些形成要求。我们侧重于当地最佳和不稳定的演变,我们纳入了新的基于模型的政策制约和人口适应战略,大大缓解了性能退化。在网络通信领域应用Moloy-Reed标准,我们开发了一种适应性地形方法,在理论上和实验上确保结点失灵情况下的连通性及其有效性得到验证。实验结果证明拟议的形成控制方法的有效性。更重要的是,我们表明将一般形成控制问题作为Markov决定程序(MDP)处理并通过迭接学习加以解决是可行的。