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On the compression of locational and environmental data in multi-vehicle missions: A control systems approach

机译:关于多车任务中位置和环境数据的压缩:一种控制系统方法

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Mobile agents that take part in multi-vehicle missions usually need to share environmental and locational information with other agents and with control stations through a communication channel. In real scenarios, the agents have to deal with different communication issues, such as interference, loss of connectivity and unexpected reduction of available bandwidth. One way to overcome these issues is by minimising the amount of data in the communication channel, which not only speeds up the sharing of information, but would also avoid the loss of data. We propose a control systems approach that allows the compression of the shared information. Given some problem-dependent mathematical assumptions, our method aims to simplify the calculation of the stationary errors by computing the sign of the errors rather than their exact values and the control law may then be used to stabilise the system. The approach allows for the compression of the outputs involved in the calculation of the errors as such outputs represent the shared information among agents. We carry out the theoretical analysis of our approach and apply it to two case studies, namely a formation control and a coverage control with consensus. We finally validate our theoretical results through simulations in Matlab.
机译:参与多车任务的移动代理通常需要通过通信通道与其他代理和控制站共享环境和位置信息。在实际情况下,代理必须处理不同的通信问题,例如干扰,连接丢失和可用带宽的意外减少。克服这些问题的一种方法是通过最小化通信通道中的数据量,这不仅可以加快信息共享的速度,而且可以避免数据丢失。我们提出了一种控制系统方法,该方法允许压缩共享信息。给定一些与问题相关的数学假设,我们的方法旨在通过计算误差的符号而不是其精确值来简化稳态误差的计算,然后可以使用控制律来稳定系统。该方法允许压缩误差计算中涉及的输出,因为这种输出表示代理之间的共享信息。我们对我们的方法进行了理论分析,并将其应用于两个案例研究,即地层控制和具有共识的覆盖率控制。我们最终通过Matlab中的仿真验证了我们的理论结果。

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