Search results for "ERT"
showing 10 items of 21537 documents
Robust link prediction in criminal networks: A case study of the Sicilian Mafia
2020
Abstract Link prediction exercises may prove particularly challenging with noisy and incomplete networks, such as criminal networks. Also, the link prediction effectiveness may vary across different relations within a social group. We address these issues by assessing the performance of different link prediction algorithms on a mafia organization. The analysis relies on an original dataset manually extracted from the judicial documents of operation “Montagna”, conducted by the Italian law enforcement agencies against individuals affiliated with the Sicilian Mafia. To run our analysis, we extracted two networks: one including meetings and one recording telephone calls among suspects, respect…
Autonomous ultrasonic inspection using Bayesian optimisation and robust outlier analysis
2020
The use of robotics is beginning to play a key role in automating the data collection process in Non Destructive Testing (NDT). Increasing the use of automation quickly leads to the gathering of large quantities of data, which makes it inefficient, perhaps even infeasible, for a human to parse the information contained in them. This paper presents a solution to this problem by making the process of NDT data acquisition an autonomous one as opposed to an automatic one. In order to achieve this, the robotic data acquisition task is treated as an optimisation problem, where one seeks to find locations with the highest indication of damage. The resulting algorithm combines damage detection tech…
Multiple Fault Diagnosis of Electric Powertrains Under Variable Speeds Using Convolutional Neural Networks
2018
Electric powertrains are widely used in automotive and renewable energy industries. Reliable diagnosis for defects in the critical components such as bearings, gears and stator windings, is important to prevent failures and enhance the system reliability and power availability. Most of existing fault diagnosis methods are based on specific characteristic frequencies to single faults at constant speed operations. Once multiple faults occur in the system, such a method may not detect the faults effectively and may give false alarms. Furthermore, variable speed operations render a challenge of analysing nonstationary signals. In this work, a deep learning-based fault diagnosis method is propos…
Robust adaptive tracking control of uncertain systems with time-varying input delays
2017
ABSTRACTIn this paper, the problem of robust adaptive tracking control of uncertain systems with time-varying input delays is studied. Under some mild assumptions, a robust adaptive controller is designed by using adaptive backstepping technique such that the system is globally stable and the system output can track a given reference signal. At the same time, a root mean square type of bound is obtained for the tracking error as a function of design parameters and thus can be adjusted. Finally, one numerical example is given to show the effectiveness of the proposed scheme.
Adaptive Control of Soft Robots Based on an Enhanced 3D Augmented Rigid Robot Matching
2021
Despite having proven successful in generating precise motions under dynamic conditions in highly deformable soft-bodied robots, model based techniques are also prone to robustness issues connected to the intrinsic uncertain nature of the dynamics of these systems. This letter aims at tackling this challenge, by extending the augmented rigid robot formulation to a stable representation of three dimensional motions of soft robots, under Piecewise Constant Curvature hypothesis. In turn, the equivalence between soft-bodied and rigid robots permits to derive effective adaptive controllers for soft-bodied robots, achieving perfect posture regulation under considerable errors in the knowledge of …
Event-triggered robust adaptive control for discrete time uncertain systems with unmodelled dynamics and disturbances
2019
In practice, modelling errors caused by high-order unmodelled dynamics and external disturbances are unavoidable. How to ensure the robustness of an adaptive controller with respect to such modelling errors is always a critical concern. In this study, the authors consider the design of event-triggered robust adaptive control for a class of discrete-time uncertain systems which involve such modelling errors and also are allowed to be non-minimum phase. Unlike some existing event-triggered control schemes, the developed controllers do not require that the measurement errors meet the corresponding input-to-state stable condition. Global stability of the closed-loop system which means that all …
A Novel Solution for the Elimination of Mode Switching in Pump-Controlled Single-Rod Cylinders
2020
This paper concerns the stability issue of pump-controlled single-rod cylinders, known as mode switching. First, a review of the topic is provided. Thereafter, the most recently proposed solution for the elimination of mode switching is investigated and shown to result in unstable behavior under certain operating conditions. A theoretical analysis is provided demonstrating the underlying mechanisms of this behavior. Based on the analysis, a novel control strategy is proposed and investigated numerically. Proper operation and stability are demonstrated for a wide range of operating conditions, including situations under which the most recently proposed solution results in unstable behavior a…
Predictive Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…
An adaptive multi-rate system for visual tracking in augmented reality applications
2016
The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracki…
Current fault signatures of Voltage Source Inverters in different reference frames
2016
This paper considers different current patterns used to identify the correct fault signatures in Voltage Source Inverters (VSI). At the beginning, the Authors consider the currents patterns from which a simple or a double fault can be encompassed both in the case of controllable device only or with its free wheeling companion diode. After the discussion of diagnosis algorithm suitable for electrical drives and principally based on a persistent near zero current condition current in the natural phase reference frame, the stationary reference frame is then considered as a tool to identify both the faulted phase as the device or various combination of faulted devices. On the contrary, the Auth…