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Distributed model predictive control for constrained multi-agent systems: a swarm aggregation approach

机译:分布式模型预测控制限制多助理系统:一种群体聚集方法

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In this paper, a distributed receding horizon control scheme is developed for teams of autonomous agents customized as swarms within platoon configurations. Coordination and collision avoidance specs for multi-agent systems prescribe the use of high memory requirements for local computations and the exploitation of a growing number of sensors as the involved agents increase. In order to mitigate such a drawback, two key ingredients are exploited: 1) the swarm formation modelling that allows to consider in some sense several agents acting as a singleton; 2) an ad hoc model predictive scheme capable to adequately exploit swarm kinematics properties to ameliorate energy consumption savings.
机译:在本文中,为分列的分布式后退地平线控制方案为分列配置中作为群体定制的自主代理团队开发。多种代理系统的协调和碰撞避免规范规定了对局部计算的高存储器要求以及随着所涉及的代理的增加,利用越来越多的传感器的开发。为了减轻这种缺点,利用了两个关键成分:1)群体形成建模,以便在某种意义上考虑一些代理作为单身的代理; 2)AD HOC模型预测方案能够充分利用群体运动学属性来改善能源消耗节省。

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