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Finite-Level Quantized Min-Consensus Control Based on Encoding-Decoding
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AI
DOI：10.1109/TCYB.2022.3169660.png)
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Abstract
En 中文
This article studies the min-consensus control of continuous-time real-valued multiagent systems, with sampled information, quantized communication, and switching topologies. Due to the limited bandwidth of the digital communication network, only finite-bit binary symbolic sequence can be exchanged among the agents. In order to realize the min-consensus control with quantized communication and limited bandwidth, a novel finite-level biased quantizer and a nonstrict decreasing scaling function are designed, and correspondingly a set of switching encoders and decoders are constructed. By means of the proposed encoders and decoders, the according sampled-data min-consensus control inputs are carefully constructed, and the memory variables are introduced into the control inputs and are monotonically decreasing no matter how the communication topology is switched. The proposed encoding-decoding-based control scheme can achieve accurate min-consensus with limited bandwidth, as long as the communication graphs are jointly strongly connected. The numerical simulations show the effectiveness of the proposed control scheme.
Keywords:
Switches
Topology
Consensus control
Bandwidth
Control systems
Decoding
Multi-agent systems
Limited communication data rates
min-consensus control
multiagent systems (MASs)
switching topologies
Journal
IF:
10.5
Papers:
1.1W
Citations:
5.0W