Shaping up crowd of agents through controlling their statistical moments
Shaping up crowd of agents through controlling their statistical moments
复制标题
通过控制统计矩来塑造智能体群体
DOI：
10.1109/ecc.2015.7330674
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Xiaoming Hu
中科院分区：
文献类型：
--
作者：
Yuecheng Yang;Dimos V. Dimarogonas;Xiaoming Hu
在基于领导者-追随者交互的人群模型中，领导者的位置被视为控制输入，最新的解决方案依赖于代理坐标的知识。在实践中，利用代理组的统计属性的知识，而不是他们的确切位置，更为现实。为了塑造人群，我们转而研究控制力矩的问题，因为众所周知，形状可以由力矩决定。通过求解修正的 Hamilton-Jacobi-Bellman (HJB) 方程获得了力矩跟踪问题的最优控制，该方程仅使用力矩和领导者状态作为反馈。最优解的求解速度足够快，适合在线实施。
In a crowd model based on leader-follower interactions, where positions of the leaders are viewed as the control input, up-to-date solutions rely on knowledge of the agents' coordinates. In practice, it is more realistic to exploit knowledge of statistical properties of the group of agents, rather than their exact positions. In order to shape the crowd, we study thus the problem of controlling the moments instead, since it is well known that shape can be determined by moments. An optimal control for the moments tracking problem is obtained by solving a modified Hamilton-Jacobi-Bellman (HJB) equation, which only uses the moments and leaders' states as feedback. The optimal solution can be solved fast enough for on-line implementations.