This paper investigates the tracking consensus issue for second order multi-agent systems (MAS) under switching topologies by using a novel event-triggered sliding mode control strategy. First, in order to compensate for the effect brought by the information transmission caused by event-triggered sampling and the switching topologies respectively, the dynamic sliding mode control (SMC) mechanism is proposed based on two discrete level sets. By considering the event-triggered rules and the sliding mode method jointly, the corresponding limited-information-based protocol is constructed. This technology does not require the system dynamics to reach the sliding mode manifold compared to previous studies. In addition, with the help of the boundary layer technique, the control protocol is designed to be continuous, which can reduce the chattering of the system and increase the life of machine. Through strict mathematical derivation, when the dwell time of switching between different communication graph candidates is within a limited range, it is proved that the consensus error of the nonlinear multi-agent systems (NMAS) with disturbances converges to an adjustable bounded set, and the networked harmonic oscillator systems (NHOS) without disturbances asymptotically reaches zero. Finally, Zeno behavior can be avoided entirely, and several numerical examples are presented to evaluate the efficiency of the proposed algorithms.

This paper investigates the observer-based event-triggered adaptive sliding mode control (SMC) problem of the semi-Markovian jumping multi-agent systems (S-MJMASs) with completely unknown and uncertain bounded transfer probabilities (TPs). As impacted by the limited bandwidth of the communication network between individual agents and the unmeasurable state information of the systems, an innovative observer based distributed event-triggered adaptive mechanism (ETAM) is proposed, in which the global information of the network is not used and the triggering threshold is dynamically regulated by the adaptive law to reduce excessive network communication. Additionally, since delays exist between the event trigger and the zero-order holder (ZOH) during data transmission in network communication systems, as well as the semi-Markovian jumping parameters, the uncertainty of systems is increased. In this paper, a novel integral sliding surface is constructed and its reachability and continuity in stochastic senses are guaranteed to withstand interferences. With the help of a stochastic semi-Markovian Lyapunov functional and numerous linear matrix inequalities (LMIs) approaches, certain adequate conditions are achieved to ensure that all agents in S-MJMASs can track the leader. Finally, certain numerical simulations are used to demonstrate the efficiency of the suggested theoretical conclusions.

This article addresses the issue of drive–response synchronization in fractional-order multi-link memristive neural networks (FMMNN) with multiple delays, under hybrid impulsive feedback control. To address the impact of multiple delays on system synchronization, an extended fractional-order delayed comparison principle incorporating impulses is established. By leveraging Laplace transform, Mittag–Leffler functions, the generalized comparison principle, and hybrid impulsive feedback control schemes, several new sufficient conditions are derived to ensure synchronization in the addressed FMMNN. Unlike existing studies on fractional-order single-link memristor-based systems, our response network is a multi-link model that considers impulsive effects. Notably, the impulsive gains ${\alpha }_i$ are not limited to a small interval, thus expanding the application range of our approach (${\alpha }_i\in (-2,0)\cup (-\infty ,-2)\cup (0,+\infty )$). This feature allows one to choose impulsive gains and corresponding impulsive intervals that are appropriate for the system environment and control requirements. The theoretical results obtained in this study contribute to expanding the relevant theoretical achievements of fractional-order neural networks incorporating memristive characteristics.

This paper deals with prespecified-time bipartite consensus (PTBC) for leaderless and leader-following multi-agent systems (MASs) via intermittent control. A unified framework for realizing prespecified-time (PT) intermittent control is developed and analyzed theoretically. On the basis of the communication network with cooperative-competitive interaction, both PTBC of leaderless MAS and leader-following MAS are considered. And the distributed controllers rather than the centralized controllers are designed to realize PTBC of the corresponding controlled systems respectively. Further, it is shown that the designed controller is uniformly bounded even though the time-varying feedback gain in the designed controller tends to infinity as time tends to the settling time. Finally, some numerical examples on actual circuit systems are represented to substantiate the validity and application of our theoretical results.