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A new hyperchaotic system which has two large positive Lyapunov exponents is presented and physically implemented. Spectral analysis shows that the system in the hyperchaotic mode has an extremely broad frequency bandwidth of high magnitudes, verifying its unusual random nature and indicating its great potential for some relevant engineering applications such as secure communications.

Complex networks have complete subgraphs such as nodes, edges, triangles, etc., referred to as cliques of different orders. Notably, cavities consisting of higher-order cliques have been found playing an important role in brain functions. Since searching for the maximum clique in a large network is an NP-complete problem, we propose using k-core decomposition to determine the computability of a given network subject to limited computing resources. For a computable network, we design a search algorithm for finding cliques of different orders, which also provides the Euler characteristic number. Then, we compute the Betti number by using the ranks of the boundary matrices of adjacent cliques. Furthermore, we design an optimized algorithm for finding cavities of different orders. Finally, we apply the algorithm to the neuronal network of C. elegans in one dataset, and find all of its cliques and some cavities of different orders therein, providing a basis for further mathematical analysis and computation of the structure and function of the C. elegans neuronal network.

SBT memristor is a physical memristor built on Sr0.95Ba0.05TiO3 nanometer film, described by a deterministic flux-controlled mathematical model. A new physical SBT-memristor-based Chua's circuit is presented in this paper, using the memristor to replace the Chua diode to connect with a negative conductance in parallel. The circuit can be well modeled by a fourth-order nonlinear system in the voltage-current domain and a third-order nonlinear system in the flux-charge domain, respectively. The dependences of the circuit stability on both the initial state value of the SBT memristor and the linear resistance in the circuit are analyzed theoretically, verified by numerical simulations, which shows that the circuit system has complex dynamics with multiple behaviors, including sink, periodic cycle, limit cycle, chaos, and some complicated transient dynamical behaviors. The new findings shed light on future research on the physical realization of the SBT-memristor-based Chua's circuit and other similar devices.

This paper addresses the robustness of a network to sustain its connectivity and controllability against malicious attacks. This kind of network robustness is typically measured by the time-consuming attack simulation, which returns a sequence of values that record the remaining connectivity and controllability after a sequence of node- or edge-removal attacks. For improvement, this paper develops an efficient framework for network robustness prediction, the spatial pyramid pooling convolutional neural network (SPP-CNN). The new framework installs a spatial pyramid pooling layer between the convolutional and fully-connected layers, overcoming the common mismatch issue in the CNN-based prediction approaches and extending its generalizability. Extensive experiments are carried out by comparing SPP-CNN with three state-of-the-art robustness predictors, namely a CNN-based and two graph neural networks-based frameworks. Synthetic and real-world networks, both directed and undirected, are investigated. Experimental results demonstrate that the proposed SPP-CNN achieves better prediction performances and better generalizability to unknown datasets, with significantly lower time-consumption, than its counterparts.

The dynamics of a complex network is generally very complicated due to the self-dynamics of the node and their interactions. Many existing conditions for reaching certain desirable dynamics in a complex network require global information of the network, for example, the spectrum of its Laplacian matrix. A challenging problem is how the network structure affects the network dynamics in a distributed way especially for directed networks, which is still unclear today. This paper investigates the impact of the network structure on a general directed complex network and develops a scheme to change the weights in a local manner to achieve a desired behavior. In particular, network synchronization is investigated, for which some distributed adaptive laws are designed on the coupling weights for reaching synchronization in a directed complex network. It is found that the directed spanning tree structure is helpful while the aggregation and circular structures are harmful for achieving network synchronization. It is also found that the designed adaptive scheme on the weight of an edge in the network depends on the relative states between the terminal node and both of its inner and outer neighboring nodes, which reveals that the local information exchange in the terminal nodes is very important for reaching synchronization in directed complex networks.

Although the whip is a common tool that has been used for thousands of years, there have been very few studies on its dynamic behavior. With the advance of modern technology, designing and building soft- body robot whips has become feasible. This paper presents a study on the modeling and experimental testing of a robot whip. The robot whip is modeled using a Pseudo-Rigid-Body Model (PRBM). The PRBM consists of a number of pseudo-rigid-links and pseudo-revolute-joints just like a multi-linkage pendulum. Because of its large number of degrees of freedom (DOF) and inherited underactuation, the robot whip exhibits prominent transient chaotic behavior. In particular, depending on the initial driving force, the chaos may start sooner or later, but will die down because of the gravity and air damping. The dynamic model is validated by experiments. It is interesting to note that with the same amount of force, the robot whip can generate a velocity more than 3 times and an acceleration up to 43 times faster than that of its rigid counterpart. This gives the robot whip some potential applications, such as whipping, wrapping and grabbing. This study also helps to develop other soft-body robots that involve nonlinear dynamics.

This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.

A novel approach for output synchronization for uncertain general complex networks with non-identical nodes is proposed. This goal can be solved applying to a small fraction of network nodes (pinned ones) a neural controller; this controller is composed of an on-line identifier based on a recurrent high-order neural network, and a sliding-mode controller. An illustrative example is included, which is composed of a network of ten nodes, with different self-dynamics, illustrating the effectiveness and good performance of the proposed control scheme.

The solar power satellite (SPS), first proposed by Dr. Peter Glaser in 1968, is a huge spacecraft capturing solar energy in space and supplying electric power to the electric grid on the ground. With the rapid progress of reusable launch technology and the ability to develop large-scale spacecraft, developing space solar power (SSP) is gradually becoming of great practical significance from both technical and economic perspectives. Many countries and organizations consider SSP to be one of the promising clean energy sources. Due to the huge size, immense mass and high-power of an SPS, there are still many technical challenges to achieve an SSP. There has been no scaled technology demonstration system developed in the world so far. According to various SPS development roadmaps proposed by various countries and organizations, technology demonstrations at different levels, including component level, subsystem level and system level, need to be carried out in space. Some small space demonstration missions have been carried out recently or will be carried out in the near future. According to a proposed SSP roadmap by Chinese experts, the key technologies related to SSP need to be demonstrated in space step by step, including high-power electricity generation, wireless power transmission (WPT), space super-large structure deployment, assembly and control. As the first step, the high-power electricity generation and WPT demonstration mission is presented in this paper. The mission will demonstrate high voltage electricity generation, kW-level microwave power transmission from lower earth orbit (LEO) to the ground, kW-level laser power transmission (LPT) from LEO to the ground and LPT between two spacecraft simultaneously, and validate the theoretical energy transmission efficiency chain and long-distance beam control precision, which will lay the foundation for the subsequent missions.