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This article presents a comprehensive study on the emerging near-space communications (NS-COM) within the context of space–air–ground–sea integrated network (SAGSIN). Specifically, we firstly explore the recent technical developments of NS-COM, followed by the discussions about motivations behind integrating NS-COM into SAGSIN. To further demonstrate the necessity of NS-COM, a comparative analysis between the NS-COM network and other counterparts in SAGSIN is conducted, covering aspects of deployment, coverage, channel characteristics, and unique problems of NS-COM network. Afterward, the technical aspects of NS-COM, including channel modeling, random access, channel estimation, array-based beam management, and joint network optimization, are examined in detail. Furthermore, we explore the potential applications of NS-COM, such as structural expansion in SAGSIN communication, civil aviation communication, remote and urgent communication, weather monitoring, and carbon neutrality. Finally, some promising research avenues are identified, including stratospheric satellite-to-ground direct links for mobile terminals, reconfigurable multiple-input multiple-output and holographic multiple-input multiple-output, federated learning in NS-COM networks, maritime communication, electromagnetic spectrum sensing and adversarial game, integrated sensing and communications, stratospheric-satellite-based radar detection and imaging, NS-COM-assisted enhanced global navigation system, NS-COM-assisted intelligent unmanned system, and free-space optical communication. Overall, this paper highlights that the NS-COM plays an indispensable role in the SAGSIN puzzle, providing substantial performance and coverage enhancement to the traditional SAGSIN architecture.

Facing the challenge of achieving the goal of carbon neutrality, China is decoupling the currently close dependence of its economy on coal use. The energy supply and demand decarbonization has substantial influence on the resilience of the coal supply. However, a general understanding of the precise impact of energy decarbonization on the resilience of the coal energy supply is still lacking. Here, from the perspective of network science, we propose a theoretical framework to explore the resilience of the coal market of China. We show that the processes of increasing the connectivity and the competition between the coal enterprises, which are widely believed to improve the resilience of the coal market, can undermine the sustainability of the coal supply. Moreover, our results reveal that the policy of closing small-sized coal mines may not only reduce the safety accidents in the coal production but also improve the resilience of the coal market network. Using our model, we also suggest a few practical policies for minimizing the systemic risk of the coal energy supply.

The development of many modern critical infrastructures calls for the integration of advanced technologies and algorithms to enhance the performance, efficiency, and reliability of network systems [...]

Hyperspectral anomaly detection represents a crucial application of intelligent sensing, focusing on the identification and localization of anomalous targets. However, the complicated background distribution of hyperspectral imagery (HSI) and the lack of exploration of the intrinsic structure raise enormous challenges for efficient anomaly detection. To address these issues, we introduce the tensor multi-subspace learning strategy with nonconvex low-rank regularization (TMNLR) for anomaly detection in HSI. The HSI is considered as a third-order tensor and is decomposed to background and anomaly, where the tensor subspace and the coefficient tensor are obtained from the background via the tensor multisubspace learning strategy. To improve detection accuracy, the nonconvex low-rank regularization is introduced for suppressing the background, where the optimization process is designed to extract the background coefficient tensor. And the nonisotropic total variation (TV) regularization is jointly implemented to maintain the local spatial similarity of HSI and promote spatial smoothness. Results demonstrate that the proposed framework could achieve an average detection accuracy rate of 97.98% on four real-scene datasets. Extensive experiments validate the effectiveness and robustness of the TMNLR over the comparative methods.

Coordinated directional switches often emerge in moving biological groups replete with individual-level interactions. Recent self-propelled particles models can somewhat mimic the patterns of directional switches, but they usually do not include the effects of time delays in the interactions. Here, we focus on investigating the influence of time-delay interactions on the collective motion of swarming locusts, an experimentally well-studied system that exhibits ordered switches between clockwise and counterclockwise movement. We show, both analytically and numerically, that time delays of different types can affect the directional switches. Specifically, for the sufficiently small response delay, increasing the transmission delay can increase the mean switching time, while, for the large response delay, increasing the transmission delay may destroy the ordered directional switches. Our results decipher the role of time-delay interactions in the collective motion, which could be beneficial to the design of collective intelligent devices.

The article focuses on a study conducted on distributed control strategies for the cooperative control of spacecraft formation. Topics discussed include two types of attitude cooperative control: the leaderless case, and the leader-following case; the problem of attitude cooperative control in multiple flexible spacecraft; and the nonlinear structure of the attitude control system, for which a Lyapunov function is used for achieving controller design.

In this study, distributed leader-following consensus for a class of second-order multi-agent systems with delayed information transmission is studied. Based on and only on the relative delayed information between neighbouring agents, two distributed consensus protocols are designed and analysed. The first one is adopted to achieve leader-following consensus for the case where both relative delayed position and velocity measurements are available for neighbouring agents. For the second case where only the relative delayed position measurements can be used for coordination, a new type of observer-based protocol is constructed. By using tools from frequency domain analysis and control theory, several necessary and sufficient conditions for the existence of such protocols under a directed communication topology are established. Finally, simulation examples are performed to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

In this study, the H∞ consensus problem of a group of linear multi-agent systems with directed communication graph is addressed. To achieve H∞ consensus, a new class of distributed consensus protocols based only on the relative states of the neighbouring agents is proposed. Compared with the existing protocols, the one presented in this study focuses on solving the H∞ consensus problem in strongly connected directed networks. By using tools from algebraic graph theory and Lyapunov stability analysis, it is theoretically shown that distributed H∞ consensus in the closed-loop multi-agent systems with strongly connected topology can be achieved if the distributed consensus protocol is appropriately designed. A twostep algorithm is then presented to construct such a protocol. The H2 consensus problem for networked systems is further investigated. Finally, the effectiveness of the theoretical analysis is verified via numerical simulations. [ABSTRACT FROM AUTHOR]

This study addresses the global pinning synchronisation of directed networks with Lorenz-type node dynamics. By using tools from M-matrix theory and Lyapunov stability theory, the interesting issues of what kind of nodes should be pinned and how large the control strength between neighbouring nodes should be selected for achieving global synchronisation in both fixed and switching networks are clearly addressed. It is theoretically shown that global pinning synchronisation of an arbitrarily given fixed network can be achieved if the network topology contains a directed spanning tree and the coupling strength is larger than a derived critical value depending both on the node dynamics and the network topology. By suitably constructing multiple Lyapunov functions, it is further proved that global pinning synchronisation in switching networks with a suitable coupling strength can be guaranteed if each possible network topology contains a directed spanning tree and the dwell time of switching is less than a positive threshold. Numerical examples are finally given for illustration. [ABSTRACT FROM AUTHOR]

This study addresses the robust consensus tracking problem of multi-agent systems with uncertain Lur'e-type nonlinear dynamics under a fixed topology. To achieve consensus tracking, a class of discontinuous control protocols are first proposed, which rely on the relative information among the neighbouring agents. Theoretical analysis indicates that the robust consensus tracking of uncertain Lur'e network can be achieved if the coupling strength and the control gain are both larger than the thresholds depending on some global information of the network. Then, an adaptive consensus tracking protocol is further designed to solve the robust consensus tracking problem as a modification of a fully distributed version without the need of any global information of the multi-agent systems. Furthermore, as an expansion of the discontinuous protocols, a new class of continuous control laws are developed based on the boundary layer concept. Finally, a couple of examples are given to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we present a local-world evolving model to characterize weighted networks. By introducing the extended links to mimic the weak interactions between the nodes in different local-worlds, the model yields scale-free behavior as well as the small-world property, as confirmed in many real networks. With the increase of the local information, the generated network undergoes a transition from assortative to disassortative, meanwhile the small-world property is preserved. It indicates that the small-world property is a universal characteristic in our model. The numerical simulation results are in good agreement with the analytical expressions. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the concept of intrinsic strength which is used to describe the node's intrinsic property. Furthermore, we present a single preferential attachment model for the evolution of weighted networks in which the network growth is coupled with dynamical evolution of weights and intrinsic strength. The model yields a nontrivial time evolution of nodes' properties and generalized power law distributions for the weight, strength and degree, as confirmed in many real networks. The numerical simulation results are in good agreement with the analytical expressions. [ABSTRACT FROM AUTHOR]

In this paper, the new decoupled distributed sliding-mode control (DSMC) is first proposed for second-order consensus in multiagent systems, which finally solves the fundamental unknown problem for sliding-mode control (SMC) design of coupled networked systems. A distributed full-order sliding-mode surface is designed based on the homogeneity with dilation for reaching second-order consensus in multiagent systems, under which the sliding-mode states are decoupled. Then, the SMC is applied to the decoupled sliding-mode states to reach their origin in finite time, which is the sliding-mode surface. The states of agents can first reach the designed sliding-mode surface in finite time and then move to the second-order consensus state along the surface in finite time as well. The DSMC designed in this paper can eliminate the influence of singularity problems and weaken the influence of chattering, which is still very difficult in the SMC systems. In addition, DSMC proposes a general decoupling framework for designing SMC in networked multiagent systems. Simulations are presented to verify the theoretical results in this paper.

This paper considers the position-based consensus in a network of agents with double-integrator dynamics and directed topology. Two types of distributed observer algorithms are proposed to solve the consensus problem by utilizing continuous and intermittent position measurements, respectively, where each observer does not interact with any other observers. For the case of continuous communication between network agents, some convergence conditions are derived for reaching consensus in the network with a single constant delay or multiple time-varying delays on the basis of the eigenvalue analysis and the descriptor method. When the network agents can only obtain intermittent position data from local neighbors at discrete time instants, the consensus in the network without time delay or with nonuniform delays is investigated by using the Wirtinger's inequality and the delayed-input approach. Numerical examples are given to illustrate the theoretical analysis.

This paper is concerned with the distributed consensus tracking problem of uncertain multiagent systems with directed communication topology and a single high-dimensional leader. Compared with existing related works, the dynamics of each follower in the present framework are subject to unmodeled dynamics and unknown external disturbances, which is more practical in various applications. Furthermore, the dimensions of leader's dynamics may be different with those of the followers' dynamics. Under the mild assumption that each follower can directly or indirectly sense the output information of the leader, a distributed robust adaptive neural network controller together with a local observer are designed to each follower to ensure that the states of each follower ultimately synchronize to the leader's output with bounded residual errors under a fixed topology. By appropriately constructing some multiple Lyapunov functions, the derived results are further extended to consensus tracking with switching directed communication topologies. The effectiveness of the analytical results is demonstrated via numerical simulations.