Self-Healing Control with Multifunctional Gate Drive Circuits for Power Converters

Many commercial and military transport systems have fault diagnostic functions implemented to help protect the device when a severe fault occurs. However, most present systems do not contain prognostics capability which would allow operators to observe an unhealthy system component in its pre- fault condition. In industry applications, scheduled downtime can result in considerable cost avoidance. The next technology step is self-healing system components which observe not only potential problems, but can also take steps to continue operation under abnormal conditions - whether due to long-term normal wear-and-tear or sudden combat damage. In this paper, current and voltage information using the double-layer gate drive concept is fed to intelligent networks to identify the type of fault and its location. These intelligent networks are based on unsupervised and supervised learning networks (self-organizing maps and learning vector quantization networks respectively). The proposed concept allows the reconfiguration of the electric machinery system for continued normal operation of the machine. This paper presents an intelligent health monitoring and self-healing control strategy for a multi-phase multilevel motor drive under various types of faults

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Modeling self-organization in pedestrians and animal groups from macroscopic and microscopic viewpoints

This paper is concerned with mathematical modeling of intelligent systems, such as human crowds and animal groups. In particular, the focus is on the emergence of different self-organized patterns from non-locality and anisotropy of the interactions among individuals. A mathematical technique by time-evolving measures is introduced to deal with both macroscopic and microscopic scales within a unified modeling framework. Then self-organization issues are investigated and numerically reproduced at the proper scale, according to the kind of agents under consideration.Comment: 24 pages, 13 figure

Self-organising comprehensive handover strategy for multi-tier LTE-advanced heterogeneous networks

Long term evolution (LTE)-advanced was introduced as real fourth generation (4G) with its new features and additional functions, satisfying the growing demands of quality and network coverage for the network operators' subscribers. The term muti-tier has also been recently used with respect to the heterogeneity of the network by applying the various subnetwork cooperative systems and functionalities with self-organising capabilities. Using indoor short-range low-power cellular base stations, for example, femtocells, in cooperation with existing long-range macrocells are considered as the key technical challenge of this multi-tier configuration. Furthermore, shortage of network spectrum is a major concern for network operators which forces them to spend additional attentions to overcome the degradation in performance and quality of services in 4G HetNets. This study investigates handover between the different layers of a heterogeneous LTE-advanced system, as a critical attribute to plan the best way of interactive coordination within the network for the proposed HetNet. The proposed comprehensive handover algorithm takes multiple factors in both handover sensing and decision stages, based on signal power reception, resource availability and handover optimisation, as well as prioritisation among macro and femto stations, to obtain maximum signal quality while avoiding unnecessary handovers

In situ analysis for intelligent control

We report a pilot study on in situ analysis of backscatter data for intelligent control of a scientific instrument on an Autonomous Underwater Vehicle (AUV) carried out at the Monterey Bay Aquarium Research Institute (MBARI). The objective of the study is to investigate techniques which use machine intelligence to enable event-response scenarios. Specifically we analyse a set of techniques for automated sample acquisition in the water-column using an electro-mechanical "Gulper", designed at MBARI. This is a syringe-like sampling device, carried onboard an AUV. The techniques we use in this study are clustering algorithms, intended to identify the important distinguishing characteristics of bodies of points within a data sample. We demonstrate that the complementary features of two clustering approaches can offer robust identification of interesting features in the water-column, which, in turn, can support automatic event-response control in the use of the Gulper