The authors address control system design based on an interval observer for non‐linear switched systems with non‐linear vector functions that are assumed to satisfy Lipschitz conditions. First, the observer gain satisfying a Metzler matrix can be solved by optimisations of linear matrix inequalities (LMIs). Second, an interval observer is designed to estimate the states of non‐linear switched systems with the average dwell time scheme, and sufficient conditions for state estimation are presented in terms of an LMI formulation. Third, based on an interval observer, state feedback matrices are designed to construct an asymptotically stabilising switching controller. Finally, a numerical example is provided to demonstrate the efficiency of the approach.

Object detection is essential for an autonomous driving sensing system. Since the light condition is changed in unconstrained scenarios, the detection accuracy based on visible images can be greatly degraded. Although the detection accuracy can be improved by fusing visible and infrared images, existing multispectral object detection (MOD) algorithms suffer from inadequate inter-modal interaction and a lack of global dependence in the fusion approach. Thus, we propose a multispectral object detection framework called YOLO-MS by designing a Feature Interaction and Self-Attention Fusion Network (FISAFN) as the backbone network. Within the FISAFN, correlations between two modalities are extracted by the Feature Interaction Module (FIM) for reconstructing the information components of each modality and enhancing capability of information exchange. To filter redundant features and enhance complementary features, long-range information dependence between two modalities are established by using a Self-Attention Feature Fusion Module (SAFFM). Thus, a better information richness of the fused features can be achieved. Experimental results on the FLIR-aligned dataset and the MFD dataset demonstrate that the proposed YOLO-MS performs favorably against state-of-the-art approaches, including feature-level fusion and pixel-level fusion. And further, the proposed YOLO-MS possesses good detection performance under diverse scene conditions.

The application of Cyber-Physical System (CPS) and edge computing in smart logistics systems has greatly improved the work efficiency. This paper mainly focuses on the planning and scheduling problems in the Cyber-Physical System based multiple Automatic Guided Vehicles (multi-AGVs) logistics system. A virtual network map with uneven time constraints is firstly proposed, which realizes the control and interaction of actual work in the control layer. Then, an improved A* path planning algorithm based on the characteristics of the path network model is implemented. A novel traffic control method is added to the planning process to achieve time-sensitive and proactive scheduling and collision avoidance. Results of the numerical experiments reveal that the proposed Cyber-Physical System based heuristic method could be effectively applied to the multiple automatic guided vehicles logistics system to further improve system security as well as work efficiency.

Driven by the IoT technology and smart sensors development in Industry 5.0, the digital twin as an innovative information technology brings new opportunities and challenges for intelligent maritime logistics management. This paper tries to present a systematic review on digital twin-empowered smart maritime logistics management by employing a bibliometric analysis framework under the Industry 5.0 era. The 3372 related publications from the Web of Science database are collected as research samples from 2003 to 2023. Besides, the VosViewer is adopted to perform the co-word and network analysis by visualizing interactive collaborations of published literature. Specifically, more than 3,000 articles on maritime logistics were reviewed to determine the research trajectories and main themes through same-word study and co-citation analysis. Results show that most publications on maritime logistics management are concentrated in China and the United States, where maritime logistics is developing towards digitization and informatization. In particular, Sustainability, Maritime Policy & Management, and Journal of Marine Science and Engineering are the most important journals focusing on maritime logistics management. Moreover, we hope this review study serves as a future direction on digital twin-empowered smart maritime logistics management practices for both researchers and practitioners.

An equivalent linear matrix inequality (LMI) representation of bounded real lemma (BRL) for linear continuous-time systems is introduced. As to LTI system including polytopic-type uncertainties, by using a parameter-dependent Lyapunov function, there are several LMIs-based formulations for the analysis and synthesis of performance. All of these representations only provide us with different sufficient conditions. Compared with previous methods, this new representation proposed here provides us the possibility to obtain better results. Finally, some numerical examples are illustrated to show the effectiveness of proposed method.