In this article, we propose a continuous-time multidimensional opinion dynamics model over a social network, incorporating heterogeneous logic matrices that capture interdependencies among multiple topics. The social network comprises an influence network with cooperative and antagonistic relationships and a family of logic networks, where the influence network reflects the interpersonal interactions among individuals. In the continuous-time setting, we show that the connectivity of the social network is fully determined by the connectivity of the influence and logic networks. By employing the structural balance theory, we establish a modulus consensus of the opinion dynamics on strongly connected networks. Moreover, if the influence network contains a directed spanning tree or the logic matrices are reducible, we derive sufficient conditions for exponential convergence of the proposed model. Simulation results are provided to demonstrate and validate the analytical conclusions.

Different from continuous-time or discrete-time (CoD-T) systems, time scale-type systems (TTSs) can operate in a continuous-discrete mode, bridging the gap between continuous and discrete states. As a result, conventional methods such as the average impulsive interval (AII) and the impulsive density function (IDF) are not suitable for characterizing the frequency of impulses (FoI) required for stability analysis of TTSs with impulses. This is due to the possibility that all impulses may fall into the complementary set of time scales. In light of this, the number of impulses satisfying AII or IDF may not be sufficient to ensure stability. In response to this challenge, we introduce a novel definition in this paper, termed time scale-type impulsive density (TTID). The key feature of TTID lies in the consideration of the graininess function, which is determined by time scales, allowing for a more accurate characterization of the number of impulses required for the stability of the TTSs. Employing the proposed TTID, the criteria of asymptotical stability are presented for TTSs with stochastic and Markov-type impulses, respectively. The results presented in this paper encompass and generalize the discoveries of some existing CoD-T impulsive systems, which can be regarded as special cases of our results. We shed new light on the advantages of the TTID and the effectiveness of the theoretical results by an application of voltage control for micro-grids.

This article tackles the sampled-data control issue for a class of time-scale-type systems (TSTSs) subject to denial-of-service (DoS) attacks. A novel sampled-data control protocol, that incorporate the backward-jump-like operator (BJLO), is proposed to ensure compatibility with the discontinuity of time scales. Furthermore, a generalized Halanay-like inequality (GHLI) is proposed to address the effects of time scale discontinuities and DoS attacks on sampling intervals. Compared with the common Halanay inequality (CHI) used in continuous-time sampled-data systems, the GHLI accommodates TSTSs and permits some sampling intervals that exceed the constraints of the CHI. By leveraging the GHLI and the proposed sampled-data control protocol, the exponential stability criterion is derived for TSTSs under DoS attacks. This article culminates with two simulation examples and the micro-grid case study conducted to validate the proposed results.

This article investigates the almost sure consensus (ASC) problem for sampled-data multiagent systems (MASs) operating over semi-Markov switching networks (SMSNs) and facing different types of denial-of-service (DoS) attacks. During real-time information exchange among agents, communication failures between agents occur randomly, which may result in each possible network topology occurring with a certain probability, and its sojourn time is also stochastic. This necessitates the consideration of a more general switching signal to describe the stochastic switching phenomenon of networks. In pursuit of this goal, a semi-Markov chain is introduced to characterize the switching signal of stochastic interaction networks, whose sojourn time distribution allows for arbitrary continuous-time distribution and depends on the current and next state. Additionally, this article delves into the impact of two distinct types of DoS attacks on MASs. The first type involves random DoS attacks, which are also modeled by a semi-Markov chain to capture the stochastic nature of attack durations. The second type is deterministic DoS attacks, characterized by their frequency and duration. The proposed new stochastic analysis method, based on the law of large numbers, is used to analyze the ASC for MASs featuring SMSNs under the DoS attacks. The effectiveness of the proposed approach is demonstrated by evaluating the results obtained from two illustrative numerical examples.

With the commercial use of the fifth generation (5G), the rapid popularization of mobile Over- The- Top (OTT) voice applications has brought high-quality voice communication methods to users. The intelligent Internet in the 5G era makes communication terminals not limited to mobile phones. The complex communication environment has higher requirements for the security of data transmission between various terminals to prevent the system from being monitored or breached. At present, many OTT users use encrypted proxy technology to get rid of certain restrictions of network operators, prevent their private information from leaking, and ensure communication security. However, in some cases the encryption proxy may be subject to configuration error or maliciously attacked makes the encryption ineffective. The resulting abnormal proxy traffic may cause privacy leakage when users use voice services. However, little effort has been put on fingerprint the effectiveness of encryption for proxy voice traffic in a 5G environment. To this end, we adopt the VGG deep learning method to identify agent speech traffic, compare it with common deep learning methods, and study the impact on model performance with less abnormal traffic. Extensive experimental results show that the deep learning method we use can identify abnormal encrypted proxy voice traffic with the accuracy up to 99.77%. Moreover, VGG outperform other DL methods on indentifying the encryption algorithms of normal encrypted proxy traffic.

This paper presents a six-limb high-speed parallel robot for pick-and-place operations that is based on two Delta robots, where the two sub-platforms are connected by a gearbox. Unlike the current 6-axis Delta-type robot, all the actuators of the robot are mounted on a base platform, allowing to reduce the inertia for high dynamic performance. Besides the 3-axis translations, the three rotations of the robot end-effector are realized by the differential motions of the two sub-platforms in three directions for large orientational workspace, but without significantly increased structural complexity of gearbox, compared to the existing one. The kinematic problems are studied to reveal that the workspace volume of the robot is similar to the commercial Delta-type robots. The simplified dynamic model is established and the simulation results show that the robot can reach up to a 20G acceleration subject to the commercial actuation combination.

This paper presents stiffness analysis of a family of three/four degree-of-freedom pick-and-place robots with four identical limbs. The Cartesian stiffness matrix of the robots is modeled with the virtual spring approach. By means of a nondimensionalization of the stiffness matrix, the 6 × 6 inhomogeneous stiffness matrix is decomposed into two homogeneous sub-matrices, of which two performance indices, corresponding to the translational and rotational stiffnesses, are defined to evaluate the stiffness behaviors of the manipulators. A comparative study among the robot counterparts is carried out with respect to the elasto-static performance.

This paper deals with the parametric optimum design of a parallel Schoenflies-motion robot, named "Ragnar", designed for fast and flexible pick-and-place applications. The robot architecture admits a rectangular workspace, which can utilize the shop-floor space efficiently. In this work, the parametric models of the transmission quality, elasto-statics and dynamics are established. By taking into consideration of design requirements and pick-and-place trajectory, a comprehensive multi-objective optimization problem is formulated to optimize both kinematic and dynamic performances. The Pareto-front is obtained, which provides optimal solutions to the robot design. Robot prototyping work based on the optimal results is described.