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  Subjects -> ELECTRONICS (Total: 207 journals)
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IET Cyber-Physical Systems : Theory & Applications
Number of Followers: 1  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2398-3396
Published by IET Homepage  [46 journals]
  • Tutorial on the generation of ergodic trajectories with projection-based
           gradient descent

    • Authors: Louis Dressel;Mykel J. Kochenderfer;
      Pages: 89 - 100
      Abstract: A vehicle trajectory is ergodic with respect to some spatial distribution if the time spent in a region is proportional to the region's integrated density. One method of generating ergodic trajectories is projection-based trajectory optimisation, a gradient descent method that supports non-linear dynamics and balances trajectory ergodicity with control effort. In this study, the authors survey the existing literature on projection-based trajectory generation, focusing on implementation. They introduce an easy-to-use, open-source software package that generates ergodic trajectories orders of magnitude faster than previously reported. The authors' goal is to simplify the implementation of projection-based ergodic control so it can be applied widely across disciplines.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Review of the false data injection attack against the cyber-physical power
           system

    • Authors: Qi Wang;Wei Tai;Yi Tang;Ming Ni;
      Pages: 101 - 107
      Abstract: With the development of synchronous measuring technology and communication technology, the units of measurement, calculation, execution and communication are deeply integrated into energy manage system, which can achieve panoramic state awareness through the fast and accurate state estimation algorithm. Meanwhile, the cyber-attack has become an important issue posing severe threats to the secure operation of power systems. A well-designed false data injection attack (FDIA) against state estimation can effectively bypass the traditional bad data detection methods and interfere with the decision of the control centre, thus causing the power system incidents. This study comprehensively discusses the characteristics of FDIA including not only the goals, construction methods and consequences of FDIA from the perspective of attackers but also the protection and detection countermeasures from the perspective of defenders. Moreover, a game-theory-based FDIA against the substation information network is simulated to reveal the interactions between attackers and defenders.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Flocking-based adaptive granular control strategy for autonomous
           microgrids in emergency situations

    • Authors: Moein Sabounchi;Jin Wei;Dongchan Lee;Deepa Kundur;
      Pages: 108 - 119
      Abstract: In this study, the authors study the operation of autonomous microgrids (MGs) in emergency situations such as the presence of large physical disturbances or cyber attacks. Traditional approaches to enhance system-wide stability, such as automatic generation control, are insufficient for stabilising MGs in some emergency situations due to the correspondingly lower capacity of distributed energy resources. To address this challenge, in this study, they develop an adaptive flocking-based framework that provides control-based MG resilience. The contribution of the authors' work is three-fold. First, they effectively model the complex and dynamic dependencies amongst MG components by exploiting flocking theory. Second, they propose an adaptive granular control strategy based on the modelled dynamic dependencies. Third, they also explore the role of energy storage systems to facilitate distributed generations in achieving autonomous MG power balance in the presence of disruptions of different natures. Case studies demonstrate the effectiveness of the proposed strategy in stabilising MGs in response to physical disturbances and cyber attacks.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Performance validation of vehicle platooning through intelligible
           analytics

    • Authors: Maurizio Mongelli;Enrico Ferrari;Marco Muselli;Alessandro Fermi;
      Pages: 120 - 127
      Abstract: The study deals with intelligible analytics for performance modelling of vehicle platooning. Knowledge extraction with rules is targeted to understand safety regions (collision avoidance) of system parameters. Results are shown by feeding data through simulation to the train of different rule extraction mechanisms. Safety regions are evidenced on test data with statistical error very close to zero.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Fault data injection attack on car-following model and mitigation based on
           interval type-2 fuzzy logic controller

    • Authors: Prabhakar Gunasekaran;Selvaperumal Sundaramoorthy;Nedumal Pugazhenthi Pulikesi;
      Pages: 128 - 138
      Abstract: Cyber defence mechanism is started with modelling the accurate car-following behaviour including cyber attack. The creation of finest models made the path of control action easier. The connection between the vehicles is mathematically formulated with the help of car-following behaviour, incorporating the derived acceleration function from the cruise control physical system. The modified car-following model is simulated as closed-loop control system to analyse its behaviour in terms of acceleration and distance. Fault data injection cyber attack is mathematically injected into the modified car-following model and simulated to analyse the impact of attack. Initially, the impact of fault data injection attack is detected and mitigated with the help of parallel proportional-integral-derivative controller and genetic algorithm tuned proportional-integral-derivative controller. Interval type-2 fuzzy proportional-integral-derivative controller is introduced to mitigate the cyber attack and to overcome the uncertainty. The integral square error and integral absolute error are used to compare the performance of the controllers. Inbuilt Wi-Fi connected car like mobile robots are used in real-time model. This model is designed and developed based on the Node MCU processors, real-time operating system, sensors and actuators.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Inflow and outflow stenoses screening on biophysical experimental
           arteriovenous graft using big spectral data and bidirectional associative
           memory machine learning model

    • Authors: Chia-Hung Lin;Wei-Ling Chen;Chung-Dann Kan;
      Pages: 139 - 147
      Abstract: Long-term repeating traumatic puncture is required for dialysis therapy, which results in frequent thrombosis and graduate vascular access stenosis, such as inflow or outflow stenosis and coexistence of both. An arteriovenous graft has a higher patency rate than an arteriovenous fistula. This study intends to use the dual-channel auscultation-based non-invasive method to screen inflow and outflow stenoses. Frequency analysis is used to decompose phonoangiography (PAG) signals to frequency features using the different data length of acoustic data. Burg autoregressive method is employed to extract the key frequency parameters from sufficient spectral data, including characteristic frequencies and distinct peaks of power spectral densities (PSDs). In big data processing, PSDs and the degree of stenosis (DOS) have been validated to show a positive correlation with sufficient big spectral data. An intelligent machine learning model, bidirectional hetero-associative memory network (BHAMN), is carried out to identify the level of DOS at the inflow site, the mid-site, or the outflow site of a vascular access. The experimental results will indicate that the proposed intelligent machine learning model has higher hit rates.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Assessing cyber-physical systems to balance maintenance replacement
           policies and optimise long-run average costs for aircraft assets

    • Authors: Marco Andreacchio;Abdelghani Bekrar;Rachid Benmansour;Damien Trentesaux;
      Pages: 148 - 155
      Abstract: Many aircraft assets are subject to both preventive (scheduled) and corrective (unscheduled) replacement policies to ensure adequate levels of reliability and availability. The problem, particularly for assets that exist in large quantities, is that preventive replacement tasks often involve removing the entire population of assets from the aircraft, regardless of whether any assets were previously replaced on a corrective basis beforehand. To avoid the costs associated with premature asset removal, this study assesses the use of a cyber-physical systems approach to the management of identified aircraft assets. This approach builds on an industrial architecture that has been implemented and deployed in the aviation maintenance environment. This study outlines how the cyber-physical based identification of assets can facilitate balancing maintenance replacement policies to optimise long-run average costs per unit time. A mathematical model is proposed, and the suggested approach is validated using industrial data.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Towards a cyber physical system for personalised and automatic OSA
           treatment

    • Authors: Giovanna Sannino;Ivanoe De Falco;Giuseppe De Pietro;
      Pages: 156 - 163
      Abstract: Obstructive sleep apnoea (OSA) is a breathing disorder that takes place in the course of the sleep and is produced by a complete or a partial obstruction of the upper airway that manifests itself as frequent breathing stops and starts during the sleep. The real-time evaluation of whether or not a patient is undergoing OSA episode is a very important task in medicine in many scenarios, as for example for making instantaneous pressure adjustments that should take place when Automatic Positive Airway Pressure devices are used during the treatment of OSA. Here, the design of a possible Cyber Physical System (CPS) suited to real-time monitoring of OSA is described, and its software architecture and possible hardware sensing components are detailed. It should be emphasised here that this study does not deal with a full CPS, rather with a software part of it under a set of assumptions on the environment. The study also reports some preliminary experiments about the cognitive and learning capabilities of the designed CPS involving its use on a publicly available sleep apnoea database.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Mind your thoughts: BCI using single EEG electrode

    • Authors: Sujay Narayana;RangaRao Venkatesha Prasad;Kevin Warmerdam;
      Pages: 164 - 172
      Abstract: These days, the Internet of things (IoT) research is driving large-scale development and deployment of many innovative applications. IoT has indeed brought many smart applications to the doorstep of users. IoT has also made it possible to connect many sensors and control equipment. Here, the authors address an important application for physically challenged. The authors present a brain-computer interface (BCI) system to lock/unlock a wheelchair and control its movements using BCI. The approach presented here uses NeuroSky's MindWave Mobile, a single electrode electroencephalography (EEG) headset that can be connected to any Bluetooth-enabled system. The raw EEG data from the headset is processed on an Android mobile device to extract the electromyography (EMG) patterns that occur due to eye blinks and activity of muscles in the jaw. These patterns are used to control the movement of a wheelchair in all possible directions. A biometric security system is provided to lock and unlock the wheelchair by extracting the information about different brain waves from the raw EEG signal. In this system, only the user knows the password which is generated using brain waves and it can lock/unlock the wheelchair and control it. The proposed system was verified and evaluated using a prototype.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Cyber–physical microgrid components fault prognosis using
           electromagnetic sensors

    • Authors: Tanushree Agarwal;Payam Niknejad;Abolfazl Rahimnejad;M.R. Barzegaran;Luigi Vanfretti;
      Pages: 173 - 178
      Abstract: Higher operational requirements in cyber-physical microgrid system stress the electrical system and may push it to the edge of stability. Therefore, prognosis of the imminent failures is vital. Accessing stray electromagnetic waves of power components helps in power system protection and non-intrusive prognosis of electric components faults in a cyber-physical microgrid environment. This study implements a cyber-physical approach associated between the electromagnetic waves radiated by components in the microgrid and the communication structure. To verify the same, the entire system is implemented on a real-time lab-based microgrid environment. The major problem with the stray electromagnetic waves is receiving appropriate fields. This is resolved by placing magnetic coil antennas at optimal distances and monitoring the radiated electromagnetic waves and their harmonics. Quick response code recognition technique is used to recognise the source and its corresponding healthy mode while harmonic analysis through artificial neural network helps to find the type and origin of faults. This would be an artificial intelligence-enabled system which self-optimises and acts according to the patterns. The proposed monitoring system can be utilised in any cyber-physical microgrid system especially those located in extreme/remote areas.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
  • Energy theft detection for AMI using principal component analysis based
           reconstructed data

    • Authors: Sandeep Kumar Singh;Ranjan Bose;Anupam Joshi;
      Pages: 179 - 185
      Abstract: To detect energy theft attacks in advanced metering infrastructure (AMI), we propose a detection method based on principal component analysis (PCA) approximation. PCA approximation is introduced by dimensionality reduction of high dimensional AMI data and the authors extract the underlying consumption trends of a consumer that repeat on a daily or weekly basis. AMI data is reconstructed using principal components and used for computing relative entropy. In the proposed method, relative entropy is used to measure the similarity between two probability distributions derived from reconstructed consumption dataset. When energy theft attacks are injected into AMI, the probability distribution of energy consumption will deviate from the historical consumption, so leading to a larger relative entropy. The proposed detection method is tested under different attack scenarios using real-smart-meter data. Test results show that the proposed method can detect theft attacks with high detection percentage.
      PubDate: 6 2019
      Issue No: Vol. 4, No. 2 (2019)
       
 
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