We consider control strategies for large--scale interacting agent systems under uncertainty. The particular focus is on the design of robust controls that allow to bound the variance of the controlled system over time. To this end we consider $\mathcal{H}_\infty$ control strategies on the agent and mean field description of the system. We show a bound on the $\mathcal{H}_\infty$ norm for a stabilizing controller independent on the number of agents. Furthermore, we compare the new control with existing approaches to treat uncertainty by generalized polynomial chaos expansion. Numerical results are presented for one-dimensional and two--dimensional agent systems.
翻译:我们考虑的是大规模互动剂系统的控制策略不确定。 特别重点是设计强有力的控制策略, 以控制受控系统随时间推移产生的差异。 为此, 我们考虑对系统的代理物和平均外貌描述使用$mathcal{H ⁇ infty$的控制策略。 我们用$mathcal{H ⁇ infty$来约束一个独立于代理物数量的稳定控制器。 此外, 我们比较了新控制与现有方法, 以便通过普遍的多边混杂扩大处理不确定性。 数字结果为一维和二维的代理物系统提供 。