Finite-Time Event-Triggered Output Consensus of Heterogeneous Fractional-Order Multiagent Systems With Intermittent Communication

An event-triggered sliding mode control mechanism to exponential consensus of fractional-order descriptor nonlinear multi-agent systems

“…If functions ϕ ( t ) and f ( ϕ ( t ) ) are C-regular, 32 set V ( t ) = f ( ϕ ( t ) ) , α , β ∈ ( 0 , 1 ) and η > 0 . If…”

“…Recently, some consensus control strategies based on event-triggered mechanism including adaptive fuzzy consensus, finitetime output consensus, leader-following consensus, leader-following exponential consensus, and so on have been developed for both MAS and FO-MASs. [30][31][32][33] For example, the authors Wang and Dong 31 considered an adaptive fuzzy consensus problem of FO-MASs based on event-triggered strategy, and the boundedness of tracking errors was given. As for FOD-LMASs, the authors in the study by Zhang et al 33 investigated the leader-following exponent consensus control problem combined with an event-triggered mechanism.…”

Fuzzy adaptive observer–based resilient formation control for heterogeneous multiple unmanned aerial vehicles with false data injection attacks and prescribed performance

“…For example, the formation systems usually require reconnaissance and attack UAVs to cooperate in search-attack missions (Zhen et al, 2019). Some remarkable attempts are committed to solving cooperative control for heterogeneous multi-UAV systems or MAS, which involve but are not limited to finite-time approach (Zamanian et al, 2022), adaptive radial basis function neural network (Ren et al, 2021), reinforcement learning strategy (Liu et al, 2020), optimal control (Wang et al, 2021), event-triggered control (Gao et al, 2021), and distributed consistency estimator–based control scheme (Chen et al, 2022; Yan et al, 2022; Zou and Meng, 2019). However, these heterogeneous formation control strategies assumed that the exact system models should be known, which is quite restrictive in practical application due to the complex dynamics of UAVs.…”

“…Different from the formation control approaches in Shao et al (2022), Han et al (2021), Rosa et al (2019), Dehghani and Menhaj (2016), Zhang et al (2019), Zamanian et al (2022), Ren et al (2021), Liu et al (2020), Wang et al (2021), Gao et al (2021), Zou and Meng (2019), Yan et al (2022), and Chen et al (2022), the transient formation error constraint of each UAV can be guaranteed by a novel PPC method, which satisfies the demands in safe operation. Meanwhile, the requirement for initial states in the traditional PPC method (Ma et al, 2021; Tong et al, 2015; Zhang et al, 2016; Zhao et al, 2018; Zhou et al, 2020; Zhu et al, 2022) can be completely relaxed.…”