Sampled Data‐Based Consensus in the Presence of Asymmetric Heterogeneous Actuator Saturation
Juan Qian, Xiaoling Wang, Daniele Astolfi, Housheng Su, Guo‐Ping Jiang · International Journal of Robust and Nonlinear Control · 2025
ABSTRACT In this article, we investigate the problem of consensus of multi‐agent systems in the presence of input saturation constraints and sampled data control. An improved low‐gain feedback strategy is proposed for achieving semi‐global consensus while mitigating the adverse effects of saturation. Furthermore, a distributed dynamic saturation reconstruction protocol is designed to tackle the global consensus problem in systems with asymmetric heterogeneous actuator saturation. The results in these two approaches reveal a novel aspect by providing an explicit upper bound for the sampling periods of heterogeneous saturated agents, posing difficulties to consensus analysis schemes. These findings, as shown in simulations, contribute to advancing the understanding and implementation of consensus in multi‐agent systems.