This research demonstrates event-triggered formation control in nonholonomic mobile robots, suggesting that fuzzy logic can enhance tracking accuracy.
This article studies the fuzzy adaptive event-triggered (ET) formation control problem for nonholonomic mobile robots (NMRs) under jointly connected switching networks. In order to solve the problem of unknown leader information in joint connected switching network, a distributed ET reference generator based on ET mechanism is constructed to estimate leader information. At the same time, the network channel utilization is optimized and the continuous information transmission between robots is avoided. Subsequently, unknown nonlinear functions in robotic dynamics can be approximate by using fuzzy logic systems (FLSs), and propose a fuzzy adaptive ET formation control algorithm only using intermittent communication by backstepping control methodology. The derivation proves that all closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB), and the tracking errors converge to a small neighborhood near zero. Finally, the simulations verify the effectiveness of the proposed formation control scheme.
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Wang et al. (2025) studied this question.
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