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Special Issue "10th Anniversary of Electronics: New Advances in Systems and Control Engineering"

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A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 26093

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Special Issue Editors

Prof. Dr. Hamid Reza Karimi

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Guest Editor

Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy
Interests: control theory; mechatronics; sensors and actuators; motion control; vibration control; vehicle dynamics; fault detection; health monitoring; wind energy
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Dr. Cheng Siong Chin

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Guest Editor

Intelligent Systems Design, Newcastle University, Singapore 038986, Singapore
Interests: intelligent systems design of complex systems in uncertain environments (underwater/electric vehicle; battery; PV system; acoustic enclosure; and water distribution network) involving predictive analytics (data mining; predictive modeling; machine learning)
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Prof. Dr. Kalyana C. Veluvolu

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NCBS Lab, School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea
Interests: onlinear estimation and ﬁltering; sliding-mode control; vehicle dynamics and control; autonomous vehicle control; AI; signal processing
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Prof. Dr. Valeri Mladenov

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Department Fundamentals of Electrical Engineering, Technical University of Sofia, Kliment Ohridski St. 8, 1000 Sofia, Bulgaria
Interests: electrical engineering, electronics; artificial intelligence; neural networks; power systems; applied mathematics; signal processing
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Dr. Cecilio Angulo

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IDEAI-UPC Research Centre on Intelligent Data Science and Artificial Intelligence, Universitat Politècnica de Caytalunya, 08034 Barcelona, Spain
Interests: cognitive robotics; artificial intelligence and control
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Dr. Davide Astolfi

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Department of Engineering, University of Perugia, 06125 Perugia, Italy
Interests: wind turbines; condition monitoring; fault diagnosis; non-stationary machinery; control and monitoring; vibrations; applied statistics; numerical modelling; mechanical systems dynamics
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Prof. Dr. Jun Yang

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Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TS, UK
Interests: disturbance observer; sliding mode control; model predictive control; active disturbance rejection control; motion control; mechatronics and robotics.

Prof. Dr. Len Gelman

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School of Computing and Engineering, Department of Engineering and Technology, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
Interests: digital signal processing; structural health monitoring; condition monitoring; artificial intelligence; vibration analysis; motor current signature analysis; adaptation of diagnosis systems
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Special Issue Information

Dear Colleagues,

Electronics was founded in 2011. We are proud and excited to celebrate the 10th anniversary of the journal. To mark the occasion, this Special Issue is being launched to invite contributions from Editorial Board Members, acknowledged reviewers, and outstanding authors. The aim is to celebrate this important anniversary of the journal with high-quality papers fully dedicated to recent efforts that contribute to innovative methodologies and/or technologies in systems and control engineering and their advanced applications. Academic editors, outstanding reviewers, and top authors will be invited to submit high-quality papers to the Special Issue.

Prof. Dr. Hamid Reza Karimi
Prof. Dr. Cheng Siong Chin
Prof. Dr. Valeri Mladenov
Prof. Dr. Cecilio Angulo
Dr. Davide Astolfi
Prof. Dr. Kalyana C. Veluvolu
Prof. Dr. Len Gelman
Prof. Dr. Jun Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Adaptive control
Stochastic systems
Hybrid and switched systems
System identification
Intelligent systems
Model predictive control
Optimization algorithms
Robust control
Fault detection and diagnosis
Networked control systems
Motion control
Industrial electronic applications in robotics, vehicles, energy, manufacturing, etc

Published Papers (15 papers)

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Research

Open AccessFeature PaperArticle

An Extreme Learning Machine Based Adaptive VISMA for Stability Enhancement of Renewable Rich Power Systems

Tigor Hamonangan Nasution

Muhammad Abdillah

Prisma Megantoro

and

Awan Uji Krismanto

Electronics 2022, 11(2), 247; https://doi.org/10.3390/electronics11020247 - 13 Jan 2022

Cited by 10 | Viewed by 1401

Abstract

Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

and

Fausto Pedro García Márquez

Electronics 2021, 10(22), 2770; https://doi.org/10.3390/electronics10222770 - 12 Nov 2021

Cited by 8 | Viewed by 1084

Abstract

This article presents the control of a three-phase three-wire (3P-3W) dual-stage grid-tied PV-battery storage system using a multi-objective grass-hopper optimization (MOGHO) algorithm. The voltage source converter (VSC) control of the presented system is implemented with adaptive kernel width sixth-order maximum correntropy criteria (AKWSOMCC) and maximum power point tracking (MPPT) control is accomplished using the variable step-size incremental conductance (VSS-InC) technique. The proposed VSC control offers lower mean square error and better accuracy, convergence rate and speed as compared to peer adaptive algorithms, i.e., least mean square (LMS), least mean fourth (LMF), maximum correntropy criteria (MCC), etc. The adaptive Gaussian kernel width is a function of the error signal, which changes to accommodate and filter Gaussian and non-Gaussian noise signals in each iteration. The VSS-InC based MPPT is provided with a MOGHO based modulation factor for better and faster tracking of the maximum power point during changing solar irradiation. Similarly, an optimized gain conventional PI controller regulates the DC bus to improve the power quality, and DC link stability during dynamic conditions. The optimized DC-link generates an accurate loss component of current, which further improves the VSC capability of fundamental load current component extraction. The VSC is designed to perform multi-functional operations, i.e., harmonics elimination, reactive power compensation, load balancing and power balancing at point of common coupling during diverse dynamic conditions. The MOSHO based VSS-InC, and DC bus performance is compared to particle swarm optimization (PSO) and genetic algorithm (GA). The proposed system operates satisfactorily as per IEEE519 standards in the MATLAB simulation environment. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Adaptive Fading Extended Kalman Filtering for Mobile Robot Localization Using a Doppler–Azimuth Radar

Bin Li

Yanyang Lu

and

Hamid Reza Karimi

Electronics 2021, 10(20), 2544; https://doi.org/10.3390/electronics10202544 - 18 Oct 2021

Cited by 3 | Viewed by 1025

Abstract

In this paper, the localization problem of a mobile robot equipped with a Doppler–azimuth radar (D–AR) is investigated in the environment with multiple landmarks. For the type (2,0) robot kinematic model, the unknown modeling errors are generally aroused by the inaccurate odometer measurement. Meanwhile, the inaccurate odometer measurement can also give rise to a type of unknown bias for the D–AR measurement. For reducing the influence induced by modeling errors on the localization performance and enhancing the practicability of the developed robot localization algorithm, an adaptive fading extended Kalman filter (AFEKF)-based robot localization scheme is proposed. First, the robot kinematic model and the D–AR measurement model are modified by considering the impact caused by the inaccurate odometer measurement. Subsequently, in the frame of adaptive fading extended Kalman filtering, the way to the addressed robot localization problem with unknown biases is sought out and the stability of the developed AFEKF-based localization algorithm is also discussed. Finally, in order to testify the feasibility of the AFEKF-based localization scheme, three different kinds of modeling errors are considered and the comparative simulations are conducted with the conventional EKF. From the comparative simulation results, it can be seen that the average localization error under the developed AFEKF-based localization scheme is

{[0.0245 m 0.0224 m 0.0039 rad]}^{T}

and the average localization errors using the conventional EKF are

{[1.0405 m 2.2700 m 0.1782 rad]}^{T}

{[0.4963 m 0.3482 m 0.0254 rad]}^{T}

and

{[0.2774 m 0.3897 m 0.0353 rad]}^{T}

, respectively, under the three cases of the constant bias, the white Gaussian stochastic bias and the bounded uncertainty bias. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Modeling and Analysis of PV System with Fuzzy Logic MPPT Technique for a DC Microgrid under Variable Atmospheric Conditions

Vasantharaj Subramanian

Vairavasundaram Indragandhi

Ramya Kuppusamy

and

Yuvaraja Teekaraman

Electronics 2021, 10(20), 2541; https://doi.org/10.3390/electronics10202541 - 18 Oct 2021

Cited by 8 | Viewed by 1840

Abstract

Due to the easiness of setup and great energy efficiency, direct current (DC) microgrids (MGs) have become more common. Solar photovoltaic (PV) and fuel cell (FC) systems drive the DC MG. Under varying irradiance and temperature, this work proposes a fuzzy logic controller (FLC) based maximum power point tracking (MPPT) approach deployed to PV panel and FC generated boost converter. PV panels must be operated at their maximum power point (MPP) to enhance efficiency and shorten the system’s payback period. There are different kinds of MPPT approaches for using PV panels at that moment. Still, the FLC-based MPPT approach was chosen in this study because it responds instantaneously to environmental changes and is unaffected by circuit parameter changes. Similarly, this research proposes a better design strategy for FLC systems. It will improve the system reliability and stability of the response of the system. An FLC evaluates PV and FC via DC–DC boost converters to obtain this enhanced response time and accuracy. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Design of Composite Disturbance Observer and Continuous Terminal Sliding Mode Control for Piezoelectric Nanopositioning Stage

and

Electronics 2021, 10(18), 2242; https://doi.org/10.3390/electronics10182242 - 13 Sep 2021

Viewed by 1411

Abstract

The nonlinearities of piezoelectric actuators and external disturbances of the piezoelectric nanopositioning stage impose great, undesirable influences on the positioning accuracy of nanopositioning stage systems. This paper considers nonlinearities and external disturbances as a lumped disturbance and designs a composite control strategy for the piezoelectric nanopositioning stage to realize ultra-high precision motion control. The proposed strategy contains a composite disturbance observer and a continuous terminal sliding mode controller. The composite disturbance observer can estimate both periodic and aperiodic disturbances so that the composite control strategy can deal with the disturbances with high accuracy. Meanwhile, the continuous terminal sliding mode control is employed to eliminate the chattering phenomenon and speed up the convergence rate. The simulation and experiment results show that the composite control strategy achieves accurate estimation of different forms of disturbances and excellent tracking performance. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessFeature PaperArticle

Periodic Event-Triggered Estimation for Networked Control Systems

and

Electronics 2021, 10(18), 2215; https://doi.org/10.3390/electronics10182215 - 10 Sep 2021

Viewed by 942

Abstract

This paper considers the problem of remote state estimation in a linear discrete invariant system, where a smart sensor is utilized to measure the system state and generate a local estimate. The communication depends on an event scheduler in the smart sensor. When the channel between the remote estimator and the smart sensor is activated, the remote estimator simply adopts the estimate transmitted by the smart sensor. Otherwise, it calculates an estimate based on the available information. The closed-form of the minimum mean-square error (MMSE) estimator is introduced, and we use Gaussian preserving event-based sensor scheduling to obtain an ideal compromise between the communication cost and estimation quality. Furthermore, we calculate a variation range of communication probability, which helps to design the policy of event-triggered estimation. Finally, the simulation results are given to illustrate the effectiveness of the proposed event-triggered estimator. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessFeature PaperArticle

A Middle-Level Learning Feature Interaction Method with Deep Learning for Multi-Feature Music Genre Classification

Jinliang Liu

Changhui Wang

and

Lijuan Zha

Electronics 2021, 10(18), 2206; https://doi.org/10.3390/electronics10182206 - 09 Sep 2021

Cited by 6 | Viewed by 1909

Abstract

Nowadays, music genre classification is becoming an interesting area and attracting lots of research attention. Multi-feature model is acknowledged as a desirable technology to realize the classification. However, the major branches of multi-feature models used in most existed works are relatively independent and not interactive, which will result in insufficient learning features for music genre classification. In view of this, we exploit the impact of learning feature interaction among different branches and layers on the final classification results in a multi-feature model. Then, a middle-level learning feature interaction method based on deep learning is proposed correspondingly. Our experimental results show that the designed method can significantly improve the accuracy of music genre classification. The best classification accuracy on the GTZAN dataset can reach 93.65%, which is superior to most current methods. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Can Deep Models Help a Robot to Tune Its Controller? A Step Closer to Self-Tuning Model Predictive Controllers

Mohit Mehndiratta

Efe Camci

and

Erdal Kayacan

Electronics 2021, 10(18), 2187; https://doi.org/10.3390/electronics10182187 - 07 Sep 2021

Cited by 2 | Viewed by 1287

Abstract

Motivated by the difficulty roboticists experience while tuning model predictive controllers (MPCs), we present an automated weight set tuning framework in this work. The enticing feature of the proposed methodology is the active exploration approach that adopts the exploration–exploitation concept at its core. Essentially, it extends the trial-and-error method by benefiting from the retrospective knowledge gained in previous trials, thereby resulting in a faster tuning procedure. Moreover, the tuning framework adopts a deep neural network (DNN)-based robot model to conduct the trials during the simulation tuning phase. Thanks to its high fidelity dynamics representation, a seamless sim-to-real transition is demonstrated. We compare the proposed approach with the customary manual tuning procedure through a user study wherein the users inadvertently apply various tuning methodologies based on their progressive experience with the robot. The results manifest that the proposed methodology provides a safe and time-saving framework over the manual tuning of MPC by resulting in flight-worthy weights in less than half the time. Moreover, this is the first work that presents a complete tuning framework extending from robot modeling to directly obtaining the flight-worthy weight sets to the best of the authors’ knowledge. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Image Fusion Algorithm Selection Based on Fusion Validity Distribution Combination of Difference Features

Linna Ji

Fengbao Yang

and

Xiaoming Guo

Electronics 2021, 10(15), 1752; https://doi.org/10.3390/electronics10151752 - 21 Jul 2021

Cited by 2 | Viewed by 1296

Abstract

Aiming at addressing the problem whereby existing image fusion models cannot reflect the demand of diverse attributes (e.g., type or amplitude) of difference features on algorithms, leading to poor or invalid fusion effect, this paper puts forward the construction and combination of difference features fusion validity distribution based on intuition-possible sets to deal with the selection of algorithms with better fusion effect in dual mode infrared images. Firstly, the distances of the amplitudes of difference features between fused images and source images are calculated. The distances can be divided into three levels according to the fusion result of each algorithm, which are regarded as intuition-possible sets of fusion validity of difference features, and a novel construction method of fusion validity distribution based on intuition-possible sets is proposed. Secondly, in view of multiple amplitude intervals of each difference feature, this paper proposes a distribution combination method based on intuition-possible set ordering. Difference feature score results are aggregated by a fuzzy operator. Joint drop shadows of difference feature score results are obtained. Finally, the experimental results indicate that our proposed method can achieve optimal selection of algorithms that has relatively better effect on the fusion of difference features according to the varied feature amplitudes. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Integral Sliding Mode Anti-Disturbance Control for Markovian Jump Systems with Mismatched Disturbances

Hong Shen

Xiaoli Zhang

and

Yang Yi

Electronics 2021, 10(9), 1075; https://doi.org/10.3390/electronics10091075 - 02 May 2021

Cited by 2 | Viewed by 1193

Abstract

This paper addresses an integral sliding mode-based anti-disturbance control algorithm for a type of Markovian jump systems (MJSs), which are influenced by different types of mismatched disturbances. On one hand, as for those disturbances that can be modeled, the disturbance observer (DO) method is introduced to realize the dynamical estimation of disturbances. Based on this, both the integral sliding surface (ISS) and the composite anti-disturbance controller are proposed in succession for rejecting unknown disturbances and guaranteeing the stability of the controlled MJS. Meanwhile, the states of the controlled system are ensured to reach ISS within a finite time. In addition, the

L_{1}

performance index is given to attenuate the effects of bounded disturbances. The controller and observer gains can be computed by using convex optimization techniques. The satisfactory stochastic stability and dynamical tracking performance are both also proved. Finally, the simulation results effectively verify all of the required performances. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Open Source Control Device for Industry 4.0 Based on RAMI 4.0

and

Electronics 2021, 10(7), 869; https://doi.org/10.3390/electronics10070869 - 06 Apr 2021

Cited by 14 | Viewed by 2974

Abstract

The technical innovation of the fourth industrial revolution (Industry 4.0—I4.0) is based on the following respective conditions: horizontal and vertical integration of manufacturing systems, decentralization of computing resources and continuous digital engineering throughout the product life cycle. The reference architecture model for Industry 4.0 (RAMI 4.0) is a common model for systematizing, structuring and mapping the complex relationships and functionalities required in I4.0 applications. Despite its adoption in I4.0 projects, RAMI 4.0 is an abstract model, not an implementation guide, which hinders its current adoption and full deployment. As a result, many papers have recently studied the interactions required among the elements distributed along the three axes of RAMI 4.0 to develop a solution compatible with the model. This paper investigates RAMI 4.0 and describes our proposal for the development of an open-source control device for I4.0 applications. The control device is one of the elements in the hierarchy-level axis of RAMI 4.0. Its main contribution is the integration of open-source solutions of hardware, software, communication and programming, covering the relationships among three layers of RAMI 4.0 (assets, integration and communication). The implementation of a proof of concept of the control device is discussed. Experiments in an I4.0 scenario were used to validate the operation of the control device and demonstrated its effectiveness and robustness without interruption, failure or communication problems during the experiments. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessEditor’s ChoiceArticle

Semi-Automatic Guidance vs. Manual Guidance in Agriculture: A Comparison of Work Performance in Wheat Sowing

and

Electronics 2021, 10(7), 825; https://doi.org/10.3390/electronics10070825 - 31 Mar 2021

Cited by 8 | Viewed by 2574

Abstract

The use of digital systems in precision agriculture is becoming more and more attractive for farmers at every level. A few years ago, the use of these technologies was limited to large farms, due to the considerable income needed to amortize the large investment required. Although this technology has now become more affordable, there is a lack of scientific data directed to demonstrate how these systems are able to determine quantifiable advantages for farmers. Thus, the transition towards precision agriculture is still very slow. This issue is not just negatively affecting the agriculture economy, but it is also slowing down potential environmental benefits that may result from it. The starting point of precision agriculture can be considered as the introduction of satellite tractor guidance. For instance, with semi-automatic and automatic tractor guidance, farmers can profit from more accuracy and higher machine performance during several farm operations such as plowing, harrowing, sowing, and fertilising. The goal of this study is to compare semi-automatic guidance with manual guidance in wheat sowing, evaluating parameters such as machine performance, seed supply and operational costs of both the configurations. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Highly Robust Observer Sliding Mode Based Frequency Control for Multi Area Power Systems with Renewable Power Plants

Van Van Huynh

Bui Le Ngoc Minh

Emmanuel Nduka Amaefule

Anh-Tuan Tran

and

Phong Thanh Tran

Electronics 2021, 10(3), 274; https://doi.org/10.3390/electronics10030274 - 24 Jan 2021

Cited by 10 | Viewed by 1898

Abstract

This paper centers on the design of highly robust observer sliding mode (HROSM)-based load frequency and tie-power control to compensate for primary frequency control of multi-area interconnected power systems integrated with renewable power generation. At first, the power system with external disturbance is model in the state space form. Then the state observer is used to estimate the system states which are difficult or expensive to measure. Secondly, the sliding mode control (SMC) is designed with a new single phase sliding surface (SPSS). In addition, the whole system asymptotic stability is proven with Lyapunov stability theory based on the linear matrix inequality (LMI) technique. The new SPSS without reaching time guarantees rapid convergence of high transient frequency, tie-power change as well as reduces chattering without loss of accuracies. Therefore, the superiority of modern state-of-the-art SMC-based frequency controllers relies on good practical application. The experimental simulation results on large interconnected power systems show good performance and high robustness against external disturbances when compared with some modern state of art controllers in terms of overshoots and settling time. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

Adaptive Sliding Mode Neural Network Control and Flexible Vibration Suppression of a Flexible Spatial Parallel Robot

and

Electronics 2021, 10(2), 212; https://doi.org/10.3390/electronics10020212 - 18 Jan 2021

Cited by 11 | Viewed by 1671

Abstract

With the goal of creating a flexible spatial parallel robot system in which the elastic deformation of the flexible link causes a rigid moving platform to produce small vibrations, we proposed an adaptive sliding mode control algorithm based on a neural network. To improve the calculation efficiency, the finite element method was used to discretize the flexible spatial link, and then the displacement field of the flexible spatial link was described based on floating frame of reference coordinates, and the dynamic differential equation of the flexible spatial link considering high-frequency vibrations was established through the Lagrange equation. This was combined with the dynamic equation of the rigid link and the dynamic equation considering small displacements of the rigid movable platform due to elastic deformation, and a highly nonlinear and accurate dynamic model with a rigid–flexible coupling effect was obtained. Based on the established accurate multi-body dynamics model, the driving torque with coupling effects was calculated in advance for feedforward compensation, and the adaptive sliding mode controller was used to improve the tracking performance of the system. The nonlinear error was examined to determine the performance of the neural network’s approximation of the nonlinear system. The trajectory errors of the moving platform in the X-, Y-, and Z-directions were reduced by 12.1%, 38.8%, and 50.34%, respectively. The results showed that the designed adaptive sliding mode neural network control met the control accuracy requirements, and suppressed the vibrations generated by the deformation of the flexible spatial link. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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Open AccessArticle

A Segmented Preprocessing Method for the Vibration Signal of an On-Load Tap Changer

Rongyan Shang

Changqing Peng

and

Ruiming Fang

Electronics 2021, 10(2), 131; https://doi.org/10.3390/electronics10020131 - 09 Jan 2021

Cited by 4 | Viewed by 1613

Abstract

The vibration signal of an on-load tap changer (OLTC) consists of a series of sharp vibration bursts, and its fault feature in certain periods is easily missed. This study considered that preprocessing the vibration signal of the OLTC in segments could effectively solve the aforementioned problem. First, the collection of the signal is discussed, the waveform characteristics of the vibration signal when the OLTC was in normal action was described, and the selection of the signal was analyzed. Second, the time domain characteristics and frequency spectrum analyses were carried out to demonstrate the necessity of segmented preprocessing. Further, the segmented preprocessing method for the vibration signal of the OLTC was presented. Finally, the main mechanical faults of the OLTC were simulated, and the vibration signals were collected to carry out the fault diagnosis experiment on the OLTC. The experimental results showed that the accuracy of the fault diagnosis increased from 94.30% of the nonsegmented preprocessing to 98.46% of the segmented preprocessing. The increase was greater, especially for contact wear faults. The method was successfully applied to the actual project. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: New Advances in Systems and Control Engineering)

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