Search

For the long-range-communicated Cucker–Smale (C–S) model, asymptotic flocking can be obtained by taking full use of a key equality about the kinetic energy. However, such behavior does not exist for the short-range-communicated C–S model with general initial data. In this note, we first establish a new equality about the second-order velocity-position moments for general C–S models. Then, we use this equality to deduce a new type of asymptotic behavior for the short-range-communicated C–S model. Such behavior not only reflects an essential feature of the short-range communication weight, but also has some potential applications in the complex multicluster problem. Besides, collision avoidance is also obtained for the C–S model with some singular short-range communication weights. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of leader-follower consensus for a class of nonlinear multi-agent systems with Lipschitz-type dynamics and a directed communication topology. First, in order to reduce communication frequency among followers, an output-based event-triggered control strategy is proposed for leader-following consensus. Second, neural-network-based observers are designed to reconstruct those immeasurable information of follower agents. Third, instead of continuously monitoring follower agents’ measurements, a distributed self-triggered control strategy is put forward, which is based only on each agent’s local estimation and its previous triggered instants. Furthermore, it is proved theoretically that the consensus tracking errors are ultimately bounded and the Zeno behavior is definitely excluded. Finally, simulation results are given to show the effectiveness and advantage of the proposed results. [ABSTRACT FROM AUTHOR]

In this paper, we consider a leader-follower output consensus problem for a class of uncertain heterogeneous non-affine pure-feedback multi-agent systems (MASs) in the presence of time-delay items and input saturation restrictions under switching directed topologies. A distributed adaptive control scheme is constructed by combining Lyapunov–Krasovskii functionals, backstepping methods, neural networks (NNs), auxiliary systems, graph theory, the mean value theorem and the implicit function theory along with the dynamic surface control (DSC) technique. The key advantages of the designed control approach are that there is no requirement of precise knowledge about uncertain dynamics and time-delay items of individual agents and the computational burden can drastically be reduced by employing the DSC technique. Also, norms of unknown weight of neural networks are estimated online instead of weight vectors themselves. In theory, it can be proven that the output signals of follower agents can synchronize with the leader’s and all signals in the closed-loop system are cooperatively semiglobally uniformly ultimately bounded (CSUUB) by suitable choice of design parameters. Two simulation examples are presented to demonstrate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this paper, we study the finite-time distributed event-triggered consensus control for multi-agent systems. The controllers and the events are designed in a distributed manner, based only on local information. Compared with conventional asymptotic consensus, finite time consensus can reach consensus faster and have better disturbance rejection properties. Thus, we propose a new nonlinear distributed control protocol to achieve finite-time consensus. Moreover, in order to realize the consensus control for multi-agent systems, only the communication between the agent and its local neighbors is needed, therefore, the designed control is essentially distributed. Two sufficient conditions are proposed to reach finite-time consensus for multi-agent systems with fixed and switching network topologies, respectively. Finally, two simulation examples are presented to demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This article is concerned with bipartite tracking for a class of nonlinear multiagent systems under a signed directed graph, where the followers are with unknown virtual control gains. In the predictor-based neural dynamic surface control (NDSC) framework, a bipartite tracking control strategy is proposed by the introduction of predictors and the minimal number of learning parameters (MNLPs) technology along with the graph theory. Different from the traditional NDSC, the predictor-based NDSC utilizes prediction errors to update the neural network for improving system transient performance. The MNLPs technology is employed to avoid the problem of “explosion of learning parameters”. It is proved that all closed-loop signals steered by the proposed control strategy are bounded, and the system achieves bipartite consensus. Simulation results verify the efficiency and effectiveness of the strategy. [ABSTRACT FROM AUTHOR]

This paper addresses the consensus issue for a class of uncertain switched nonlinear multi-agent systems subject to unknown system parameters and sensor deception attacks. The actual data information is corrupted by attacks and cannot be used for the feedback control. To tackle the attacks, a set of novel auxiliary variables are introduced for the iterative design by the corrupted data. By considering the common effect of all the switching dynamics, the inherent interaction effects caused by unknown parameters, unpredictable switching and sensor deception attacks are transferred to two induced parameters. We then propose two adaptive laws to compensate the induced parameters. By constructing a common Lyapunov function, an adaptive consensus protocol is developed, under which the asymptotic output consensus of the considered uncertain systems is guaranteed regardless of deception attacks and arbitrary switching. An example is provided to illustrate the effectiveness of the established protocol. • A secure protocol is proposed for switched MASs under attacks. • Auxiliary variables are introduced by the corrupted data to tackle the attacks. • The interaction among uncertainties are transferred to two induced parameters. • The system complexity is immensely reduced. [ABSTRACT FROM AUTHOR]