Simulation study demonstrates distributed consensus control in human-in-the-loop multi-agent systems, highlighting flexible gain selection under matrix-weighted networks.
Consensus for human‐in‐the‐loop multi‐agent systems is investigated under a matrix‐weighted network. The human operator directly inputs an unmeasurable control signal to the leader, while followers in the multi‐agent system can be influenced indirectly via communication networks. To mitigate heterogeneity induced by the human operator's control inputs, a distributed consensus protocol with nonlinear term is provided for followers first, and then three different functions are introduced into the nonlinear term, respectively. Followers can choose different gains in the proposed three novel protocols, thereby enhancing the flexibility of the gain selection. Sufficient conditions for ensuring consensus under three different protocols are given, respectively. The results are verified through three comparative simulation examples.
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Wang et al. (2026) studied this question.
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