Co-Regulated Consensus of Cyber-Physical Resources in Multi-Agent Unmanned Aircraft Systems
Co-Regulated Consensus of Cyber-Physical Resources in Multi-Agent Unmanned Aircraft Systems
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DOI：
10.3390/electronics8050569
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发表时间：
2019-05
期刊：
影响因子：
2.9
通讯作者：
Chandima Fernando;Carrick Detweiler;Justin M. Bradley
中科院分区：
文献类型：
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作者：
Chandima Fernando;Carrick Detweiler;Justin M. Bradley
智能利用资源和提高自主代理的使命性能需要考虑网络和物理资源。当系统从一个代理扩展到多个代理时，这些资源的分配变得更加复杂，并且控制从集中转向分散。共识是一种分布式算法，允许多个代理就共享值达成一致，但通常不利用移动性。我们提出了一个耦合的共识控制策略，共同调节计算，通信频率和连接的代理，以实现更快的收敛时间在较低的通信速率和计算成本。在这种策略中，代理移动到一个共同的位置，以增加连接。同时，通信频率增加时，一个代理和它的连接邻居之间的共享状态错误是高的。当共享状态收敛时（即，达成共识），代理撤回到初始位置，并且通信频率降低。我们的算法的收敛性证明下提出的共同调节控制算法。我们通过一组新的网络物理，多智能体指标评估了所提出的方法，并在模拟无人驾驶飞机系统测量多个地点的温度中展示了我们的方法。结果表明，与固定速率和事件触发的共识算法相比，我们的协同调节方案可以用更少的资源实现更好的性能，同时保持对环境和系统变化的高反应性。
Intelligent utilization of resources and improved mission performance in an autonomous agent require consideration of cyber and physical resources. The allocation of these resources becomes more complex when the system expands from one agent to multiple agents, and the control shifts from centralized to decentralized. Consensus is a distributed algorithm that lets multiple agents agree on a shared value, but typically does not leverage mobility. We propose a coupled consensus control strategy that co-regulates computation, communication frequency, and connectivity of the agents to achieve faster convergence times at lower communication rates and computational costs. In this strategy, agents move towards a common location to increase connectivity. Simultaneously, the communication frequency is increased when the shared state error between an agent and its connected neighbors is high. When the shared state converges (i.e., consensus is reached), the agents withdraw to the initial positions and the communication frequency is decreased. Convergence properties of our algorithm are demonstrated under the proposed co-regulated control algorithm. We evaluated the proposed approach through a new set of cyber-physical, multi-agent metrics and demonstrated our approach in a simulation of unmanned aircraft systems measuring temperatures at multiple sites. The results demonstrate that, compared with fixed-rate and event-triggered consensus algorithms, our co-regulation scheme can achieve improved performance with fewer resources, while maintaining high reactivity to changes in the environment and system.