Design of sliding mode controller for chaotic Josephson-junction

It is known that a shunted nonlinear resistive-capacitive-inductance Josephson-junction (RCLSJ) model has a chaotic attractor. This attractor is created as a result of Hopf bifurcation that occurs when a certain direct current (DC) applied to one of the junction terminals. This chaotic attractor prevents the system from reaching the phase-locked state and hence degrade the performance of the junction. This paper aims at controlling and taming this chaotic attractor induced in this model and pulling the system to the phase-locked state. To achieve this task, a sliding mode controller is proposed. The design procedures involve two steps. In the first one, we construct a suitable sliding surface so that the dynamic of the system follows the sliding manifolds in order to meet design specifications. Secondly, a control law is created to force the chaotic attractor to slide on the sliding surface and hence stabilizes system trajectory. The RCLSJ model under consideration is simulated with and without the designed controller. Results demonstrate the validity of the designed controller in taming the induced chaos and stabilizing the system under investigation

Chaos and bifurcation in time delayed third order phase-locked loop

In this paper, the modern nonlinear theory is applied to a third order phase locked loop (PLL) with a feedback time delay. Due to this delay, different behaviors that are not accounted for in a conventional PLL model are identified, namely, oscillatory instability, periodic doubling and chaos. Firstly, a Pade approximation is used to model the time delay where it is utilized in deriving the state space representation of the PLL under investigation. The PLL under consideration is simulated with and without time delay. It is shown that for certain loop gain (control parameter) and time delay values, the system changes its stability and becomes chaotic. Simulations show that the PLL with time delay becomes chaotic for control parameter value less than the one without time delay, i.e, the stable region becomes narrower. Moreover, the chaotic region becomes wider as time delay increases

Simulation and stability of multi-port DC-DC converter

In this paper, the simulation and stability of multi-port DC-DC converter will be presented. Traditional DC-DC converter topologies interface two power terminals: a source and a load. The construction of diverse and flexible power management and distribution systems with such topologies is governed by a tight compromise between converter count, efficiency, and control complexity. The DC-DC converter may be considered as an advanced environment-friendly electronic conversion system, since it is a greenhouse emission eliminator. By utilizing the advancement of these renewable energy sources, we minimize the use of fossil fuel and thus contribute to a cleaner and pollution-free environment. Finally, comparison between the averaged model and the actual switching converter model is been studied

Phase tunable holographic fabrication for three-dimensional photonic crystal templates by using a single optical element

This paper demonstrates a phase tunable holographic fabrication of three-dimensional photonic lattice structures using a single optical element. A top-cut four-side prism is employed to generate five-beam three-dimensional interference patterns. A silica glass slide is inserted into the optical path to adjust the phase of one interfering beam relative to other four beams. The phase control of the interfering laser beam renders the lattice of the interference pattern from a face-center tetragonal symmetry into a high contrast, interconnecting diamondlike symmetry. This method provides a flexible approach to fabricating three-dimensional photonic lattices with improved photonic band structures

Deep learning-based adaptive compression and anomaly detection for smart B5G use cases operation

The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of network resources in the next decades. Among different B5G use cases, the Digital Twin (DT) has been identified as a key high bandwidth-demanding use case. The creation and operation of a DT require the continuous collection of an enormous and widely distributed amount of sensor telemetry data which can overwhelm the transport layer. Therefore, the reduction in such transported telemetry data is an essential objective of smart use case operation. Moreover, deep telemetry data analysis, i.e., anomaly detection, can be executed in a hierarchical way to reduce the processing needed to perform such analysis in a centralized way. In this paper, we propose a smart management system consisting of a hierarchical architecture for telemetry sensor data analysis using deep autoencoders (AEs). The system contains AE-based methods for the adaptive compression of telemetry time series data using pools of AEs (called AAC), as well as for anomaly detection in single (called SS-AD) and multiple (called MS-AGD) sensor streams. Numerical results using experimental telemetry data show compression ratios of up to 64% with reconstruction errors of less than 1%, clearly improving upon the benchmark state-of-the-art methods. In addition, fast and accurate anomaly detection is demonstrated for both single and multiple-sensor scenarios. Finally, a great reduction in transport network capacity resources of 50% and more is obtained by smart use case operation for distributed DT scenarios.This research was funded by the European Commission Horizon Europe SNS JU DESIRE6G project (G.A. 101096466), by the AEI through the IBON project (PID2020-114135RB-I00), and by the ICREA institution.Peer ReviewedPostprint (published version

Deep learning-based adaptive compression and anomaly detection for smart B5G use cases operation

The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of network resources in the next decades. Among different B5G use cases, the Digital Twin (DT) has been identified as a key high bandwidth-demanding use case. The creation and operation of a DT require the continuous collection of an enormous and widely distributed amount of sensor telemetry data which can overwhelm the transport layer. Therefore, the reduction in such transported telemetry data is an essential objective of smart use case operation. Moreover, deep telemetry data analysis, i.e., anomaly detection, can be executed in a hierarchical way to reduce the processing needed to perform such analysis in a centralized way. In this paper, we propose a smart management system consisting of a hierarchical architecture for telemetry sensor data analysis using deep autoencoders (AEs). The system contains AE-based methods for the adaptive compression of telemetry time series data using pools of AEs (called AAC), as well as for anomaly detection in single (called SS-AD) and multiple (called MS-AGD) sensor streams. Numerical results using experimental telemetry data show compression ratios of up to 64% with reconstruction errors of less than 1%, clearly improving upon the benchmark state-of-the-art methods. In addition, fast and accurate anomaly detection is demonstrated for both single and multiple-sensor scenarios. Finally, a great reduction in transport network capacity resources of 50% and more is obtained by smart use case operation for distributed DT scenarios.This research was funded by the European Commission Horizon Europe SNS JU DESIRE6G project (G.A. 101096466), by the AEI through the IBON project (PID2020-114135RB-I00), and by the ICREA institution.Peer ReviewedPostprint (published version

Evaluating the inertia of the Jordanian power grid

The increasing penetration of renewable energy sources in power grids has resulted in the need for a comprehensive evaluation of their impact on the dynamic behavior of the power system, including its inertia. This study aimed to evaluate the inertia of the current Jordanian power system at different penetration levels of renewable energy sources using DIgSILENT PowerFactory simulation software. In this study, the value of the constant inertia was calculated to be 8.755 s. The results were analyzed to determine the effect of renewable energy penetration on the inertia of the power system. The findings provide valuable information for the development of control strategies for integrating renewable energy sources into the Jordanian power system, ensuring stability and reliability in the power system operation. This study contributes to the understanding of the impact of renewable energy sources on power system inertia and supports the development of renewable energy integration strategies.13 página

Trends of antimicrobial resistance in Escherichia coli isolates from urine cultures of women in Jordan: A 10-year retrospective study

Background: Urinary tract infection (UTI) is a common medical condition among women. E.coli is the most common causative organism. Appropriate understanding of the development of antimicrobial resistance over the past helps to establish efficient treatment strategies in the future. The study aims to discover antimicrobial resistance trends exhibited by E.coli strains isolated from women urine cultures over the past 10 years. Methods: A total of 1874 affected urine samples over the years 2009 to 2018 were collectively reviewed and classified according to the response they showed to 24 different antimicrobial disks in the laboratory. Relations between time and resistance evolutionary profiles were calculated. Results: Gentamicin (p value =0.039), Augmentin (p value =0.017), Cefoxitin (p value =0.001), Cefixime (p value =0.026) fulfilled satisfactory figures in terms of average resistance, regression of resistance, speed of resistance evolution, steadiness of performance, side effects, spectrum range and cost with high significance. Conclusion: Drugs that showed satisfactory figures are recommended for future treatment protocols in Jordan. &nbsp

Fabrication of two-layer integrated phase mask for single-beam and single-exposure fabrication of three-dimensional photonic crystal

In this paper, we report a new design and fabrication of an integrated two-layer phase mask for five-beam holographic fabrication of three-dimensional photonic crystal templates. The phase mask consists of two layers of orthogonally oriented gratings produced in a polymer. The vertical spatial separation between two layers produces a phase shift among diffractive laser beams, which enables the holographic fabrication of interconnected three-dimensional photonic structures. A three-dimensional photonic crystal template was fabricated using the two-layer phase mask and was consistent with simulations based on the five beam interference. The reported method simplifies the fabrication of photonic crystals and is amendable for massive production and chip-scale integration of three-dimensional photonic structures. © 2008 Optical Society of American