Animals, including humans that have muscles with viscoelastic compliance can achieve improved stability. Hence, we investigate a biomimetic control framework with viscoelastic compliance and subsequently apply it to a self-balancing lower limb exoskeleton robot (SBLLER), to ensure stability during locomotion. This article presents a novel biomimetic viscoelastic compliance control framework (VCCF)

Optimizing evolving manufacturing systems often requires considering the interplay of various architectural design decisions (ADDs), especially at the lower levels of the automation pyramid. Here, decisions about programmable logic controllers, stations, and shop-floor topology directly impact product characteristics. This necessitates a multidimensional design space exploration (DSE) approach that

The rapid development of offshore wind power has led to widespread uses of high-voltage direct current (HVdc) transmission systems with long-distance dc cables. The detection and location of aged cable segment is critical for ensuring overall system reliability. As current researches mainly focus on offline location methods, a novel online detection and location scheme for modular multilevel converter

Expanding industrial components and network density raise challenges in the domain of mobility management of multiagent systems (MASs), such as multirobot cooperative transportation. This article investigates the heterogeneous network (HetNet) handover problem in the industrial context involves jointly optimizing data rate, block rate, and handover frequency among large-scale mobile user Terminals

Data-driven fault diagnosis methods suffer from restrictive assumptions that hinder adaptability to varying work conditions, rendering offline modes insufficient. Addressing this challenge, a bioinspired spike neural network (bio-SNN) is proposed, featuring an innovative online learning mode. The network employs a novel spike encoding method with data compression for efficiently transforming time series

Industrial defect detection plays a critical role in controlling product quality. Obtaining industrial defects with diverse and balanced classes in natural environments is often challenging. Most methods tend to uniformly augment all classes in small-sample datasets, which wastes computing resources and the classification performance is not always good. To achieve the purposive data augmentation, we

Internet of Things (IoT) applications have become popular and are used in innovative device applications. Although radio frequency communication methods, including Bluetooth, zonal intercommunication global standards such as ZigBee, and wireless fidelity (Wi-Fi) and wired communication such as RS485/Modbus, can be used in IoT networks, Wi-Fi is preferred by users due to its ability to connect to the

With the enablement of Internet of Things technology, the electrical grid is currently undergoing a drastic revolution, which is known as smart grid. Since massive sensitive data and control commands transmitted via public channels, the smart grid is challenged by various cyber threats. Authenticated key agreement protocols in smart grid effectively ensure the confidentiality and authentication of

Geometry-based point cloud compression (G-PCC) is a state-of-the-art point cloud compression standard. While G-PCC achieves excellent performance, its reliance on the predicting transform leads to a significant dependence problem, which can easily result in distortion accumulation. This not only increases bitrate consumption but also degrades reconstruction quality. To address these challenges, we

This article addresses the performance guaranteed consensus tracking problem for high-dimensional double-integrator multiagent systems. By integrating a dynamic surface-based back-stepping method, we propose an edge-based prescribed performance control (PPC) scheme, independent of any topology-related information. Unlike most existing works on the 1-D error constraint, the transient tracking performance

Bad road quality brings many problems, such as putting drivers and passengers in danger and causing vehicle suspension system wear. Maintaining high-quality roads relies on regular inspections and repairs, but this is a time-consuming and labor-intensive task. To improve road quality and increase the efficiency of road repairs, an Internet of Things based anomaly detection system (ADS) is proposed

This article proposes the design and verification of a novel barrier function (BF)-based adaptive composite sliding mode control method dedicated to the multiple-inputs–multiple-outputs underactuated systems. The proposed scheme is constructed by a composite sliding mode surface along with dual adaptive parameters. The main advantage of this scheme is that the actuated and underactuated state errors

Managing security threats is one of the most significant challenges when implementing Internet of Things (IoT) networks. Furthermore, most IoT applications, such as industrial IoT (IIoT), use resource-constrained devices that are also not physically protected. These facts pose severe difficulties in designing efficient security protocols. Some recent studies proposed lightweight authentication protocols

In this article, on the basis of an existing dual layer nested (DLN) adaptive sliding-mode control (ASMC) strategy, an observer-based sliding-mode control strategy with an improved DLN adaptive tuning mechanism (IDLN-ASMC) is proposed for a three-level neutral-point-clamped converter. The proposed controller not only ensures good system performance but also mitigates two problems of the existing DLN-ASMC