In this paper, the robust output consensus problem for a class of heterogeneous linear multiagent systems (MASs) in presence of aperiodic sampling and random deny-of-service (DoS) attack is investigated. A novel distributed output-feedback control strategy is proposed so that the controlled MAS achieves the objective of output consensus in spite of aperiodic sampling and DoS attack. By assuming that the sampling process is nonuniform and the consecutive attack duration is upper bounded, the closed-loop control system is first described as a discrete-time switched stochastic delay system. Some sufficient conditions are then obtained for the solvability of the secure consensus problem. Furthermore, a constructive design procedure for the proposed controller is then presented. Finally, a simulation example is introduced to illustrate the effectiveness of controller design.

Predicting the potential relations between nodes in networks, known as link prediction, has long been a challenge in network science. However, most studies just focused on link prediction of static network, while real-world networks always evolve over time with the occurrence and vanishing of nodes and links. Dynamic network link prediction (DNLP) thus has been attracting more and more attention since it can better capture the evolution nature of networks, but still most algorithms fail to achieve satisfied prediction accuracy. Motivated by the excellent performance of long short-term memory (LSTM) in processing time series, in this article, we propose a novel encoder-LSTM-decoder (E-LSTM-D) deep learning model to predict dynamic links end to end. It could handle long-term prediction problems, and suits the networks of different scales with fine-tuned structure. To the best of our knowledge, it is the first time that LSTM, together with an encoder-decoder architecture, is applied to link prediction in dynamic networks. This new model is able to automatically learn structural and temporal features in a unified framework, which can predict the links that never appear in the network before. The extensive experiments show that our E-LSTM-D model significantly outperforms newly proposed DNLP methods and obtain the state-of-the-art results.

The resilient cooperative output regulation problem for a class of uncertain nonlinear multi-agent systems (MASs) under denial-of-service (DoS) attacks is addressed in this paper. This is the first attempt to investigate the cooperative output regulation problem for nonlinear MASs under DoS attacks, and a novel distributed control scheme consisting of a resilient distributed observer and a distributed adaptive controller is proposed. Specifically, a novel resilient distributed observer in the form of an upper triangular chain of first order low pass filters is designed to estimate the exosystem state based on a composite output observability condition. Then, a distributed adaptive controller is designed. It is shown that the resilient cooperative output regulation problem for the concerned class of uncertain nonlinear MASs can be solved by the proposed control scheme. A simulation example is finally provided to show the effectiveness of the proposed control scheme.

This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators. First, a fixed-time disturbance observer (FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems. Then an adaptive scheme is used and the adaptive FTDO (AFTDO) is developed, so that the priori knowledge of the lumped disturbance is not required. Further, a new non-singular fast terminal sliding mode (NFTSM) surface is designed by using an arctan function, which helps to overcome the singularity problem and enhance the robustness of the system. Based on the estimation of the lumped disturbance by the AFTDO, a fixed-time non-singular fast terminal sliding mode controller (FTNFTSMC) is developed to guarantee the trajectory tracking errors converge to zero within a fixed time. The settling time is independent of the initial state of the system. In addition, the stability of the AFTDO and FTNFTSMC is strictly proved by using Lyapunov method. Finally, the fixed-time NFESM (FTNFTSM) algorithm is validated on a 2-link manipulator and comparisons with other existing sliding mode controllers (SMCs) are performed. The comparative results confirm that the FTNFTSMC has superior control performance.