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首页> 外文会议>Unmanned Systems Technology VIII pt.2 >Coordination Rule Design for Constrained Optimization using Mobile Sensor-Actuator Nodes
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Coordination Rule Design for Constrained Optimization using Mobile Sensor-Actuator Nodes

机译：使用移动传感器-执行器节点进行约束优化的协调规则设计

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In this paper we present ideas toward solving constrained optimization problems in a spatially-distributed mobile sensor/actuator network using decentralized computation. Notionally, each node of the network is considered to be a distributed computational unit that evolves its state according to a pre-defined rule. First, we show how to design coordination rules to ensure that the global state of the network evolves to the solution of a prescribed constrained optimization problem. Our strategy uses a recurrent neural network structure to solve the optimization problem in a global way. Next, we introduce ideas for the case when there is an absence of an all-to-all communication topology. Assuming each node can only communicate locally with its "nearest neighbors," our approach is to use the notion of a consensus variable protocol that implements a distributed observer, enabling local nodes to asymptotically obtain global information using only nearest neighbor communications. Finally, we suggest superimposing the neural network structure on top of this distributed observer to solve the global optimization problem using only local and nearest neighbor communications.
机译：在本文中，我们提出了使用分散计算来解决空间分布的移动传感器/执行器网络中的约束优化问题的想法。名义上，网络的每个节点都被认为是一个分布式计算单元，可以根据预定义的规则发展其状态。首先，我们展示如何设计协调规则，以确保网络的全局状态演变为规定的约束优化问题的解决方案。我们的策略使用递归神经网络结构以全局方式解决优化问题。接下来，我们介绍在缺少所有通信拓扑的情况下的想法。假设每个节点只能与其“最近的邻居”进行本地通信，我们的方法是使用实​​现分布式观察者的共识变量协议的概念，使本地节点仅使用最近的邻居通信就可以渐近地获取全局信息。最后，我们建议将神经网络结构叠加在此分布式观察器之上，以仅使用本地和最近邻居通信来解决全局优化问题。

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