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Advanced Control Design and Fault Diagnosis

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (30 September 2020) | Viewed by 21850

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Dr. Silvio Simani

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Guest Editor

Department of Engineering, University of Ferrara, 44122 Ferrara, Italy
Interests: system identification and data analysis; artificial intelligence; neural networks; fuzzy systems; fault diagnosis; fault tolerant control; aircraft and spacecraft systems; energy conversion systems
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Elena Zattoni

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Department of Electrical, Electronic and Information Engineering “G. Marconi” & Collegio Superiore, Alma Mater Studiorum Università di Bologna, Viale Risorgimento 2, 40136 Bologna, Italy
Interests: control theory; algorithms and optimization; automatic control; intelligent control systems; process automation and monitoring; cyber-physical systems

Special Issue Information

Dear Colleagues,

As the complexity of manufacturing and production processes increases, the role of advanced fault diagnosis and fault-tolerant control becomes more and more crucial. The development of health monitoring techniques and fault detection methods capable to early detect, or even predict, technical component malfunctioning and the synthesis of control systems that exhibit an acceptable behaviour despite the presence of failures have manifold benefits. These consist in avoiding perilous circumstances, such as endangering human beings involved in process operation or damaging the environment, preventing production downtimes, reducing costs, and improving performance.

This Special Issue will present the latest research developments and practical applications in the field of advanced fault diagnosis and control. Particularly significant contributions describing new and original achievements will be selected from the related literature, and their authors will be invited to propose enhanced versions of their works for consideration for publication in this Special Issue of Energies. The submitted manuscripts will go through the standard review process of the journal, handled by the Guest Editors.

The key aspects of the Special Issue are to present novel research developments to highlight practical applications or open problems, illustrate prototypes, and provide opportunity for the industry to hint at its needs and priorities in the areas of advanced fault diagnosis and control. New theoretical developments, as well as practical applications or industrial experiences will be covered, with the primary aims to bridge the gap between academy and industry, to foster cross-cultural exchanges, and to facilitate cooperation between the two communities.

With a standing main focus on advanced fault diagnosis and control, this Special Issue will feature topics in the related research fields, such as design for reliability and safety, support for system operation and decision-making, computational intelligence in fault diagnosis, maintenance, and repair strategies, control systems for sustainability, control reconfiguration, condition monitoring, prognosis and health management, artificial intelligence for control and diagnosis, process control, intelligent distributed discrete-event systems, intelligent methods for system identification and control, networked controlled systems, safety critical systems, intelligent sensors and actuators, transportation systems, and renewable energy systems.

Prof. Dr. Silvio Simani
Prof. Dr. Elena Zattoni
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. Energies 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 2600 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

Fault-tolerant control
Control reconfiguration
Model-based diagnosis of linear, nonlinear, and hybrid systems
Data-driven diagnosis methods
Process supervision
Diagnosis and control of discrete-event systems
Maintenance and repair strategies
Statistical methods for fault diagnosis, reliability, and safety
Condition monitoring and maintenance engineering
Prognosis and health management
Neural and fuzzy methods
Artificial Intelligence methods for control and diagnosis
Cyber-Physical Production Systems
Industrial Internet of Things
Systems and control for sustainability
Structural methods for complex systems
Distributed systems
Industrial processes
Intelligent sensors and actuators
Transportation systems
Renewable energy systems

Published Papers (10 papers)

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Editorial

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6 pages, 197 KiB

Open AccessEditorial

Advanced Control Design and Fault Diagnosis

by Silvio Simani and Elena Zattoni

Energies 2021, 14(18), 5699; https://doi.org/10.3390/en14185699 - 10 Sep 2021

Cited by 2 | Viewed by 1176

Abstract

This document provides the motivations and a brief introduction to the Special Issue entitled “Advanced Control Design and Fault Diagnosis”, which aims at presenting several solutions to the advanced control design and fault diagnosis systems. These methodologies can be considered in the general framework of advanced control, fault diagnosis and fault tolerant control systems, which are also able to improve the safety of the system under monitoring. The focuses of the current research in this field addressed in this Special Issue are also presented with emphasis on the practical application to simulated and realistic examples, which should provide an overall picture of current and future developments in this area. The works of this Special Issue represent suitably extended contributions selected by the proponents from the ACD2019—the 15th European Workshop on Advanced Control and Diagnosis, which was organised in Bologna, Italy on 21st–22nd November. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

Research

Jump to: Editorial

23 pages, 4878 KiB

Open AccessArticle

Remaining Useful Life Prediction of MOSFETs via the Takagi–Sugeno Framework

by Marcin Witczak, Marcin Mrugalski and Bogdan Lipiec

Energies 2021, 14(8), 2135; https://doi.org/10.3390/en14082135 - 11 Apr 2021

Cited by 11 | Viewed by 2134

Abstract

The paper presents a new method of predicting the remaining useful life of technical devices. The proposed soft computing approach bridges the gap between analytical and data-driven health prognostic approaches. Whilst the former ones are based on the classical exponential shape of degradation, the latter ones learn the degradation behavior from the observed historical data. As a result of the proposed fusion, a practical method for calculating components’ remaining useful life is proposed. Contrarily to the approaches presented in the literature, the proposed ensemble of analytical and data-driven approaches forms the uncertainty interval containing an expected remaining useful life. In particular, a Takagi–Sugeno multiple models-based framework is used as a data-driven approach while an exponential curve fitting on-line approach serves as an analytical one. Unlike conventional data-driven methods, the proposed approach is designed on the basis of the historical data that apart from learning is also applied to support the diagnostic decisions. Finally, the entire scheme is used to predict power Metal Oxide Field Effect Transistors’ (MOSFETs) health status. The status of the currently operating MOSFET is determined taking into consideration the knowledge obtained from the preceding MOSFETs, which went through the run-to-failure process. Finally, the proposed approach is validated with the application of real data obtained from the NASA Ames Prognostics Data Repository. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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12 pages, 3937 KiB

Open AccessArticle

The Short-Circuit Protections in Hybrid Systems with Low-Power Synchronous Generators

by Bartosz Rozegnał, Paweł Albrechtowicz, Dominik Mamcarz, Natalia Radwan-Pragłowska and Artur Cebula

Energies 2021, 14(1), 160; https://doi.org/10.3390/en14010160 - 30 Dec 2020

Cited by 9 | Viewed by 2495

Abstract

Single-phase short-circuits are most often faults in electrical systems. The analysis of this damage type is taken for backup power supply systems, from small power synchronous generators. For these hybrid installations, there is a need for standard protection devices, such as fuses or miniature circuit breaker (MCB) analysis. Experimental research mentioned that a typical protective apparatus in low-voltage installations, working correctly during supplying from the grid, does not guarantee fast off-switching, while short-circuits occur during supplication from the backup generator set. The analysis of single-phase short-circuits is executed both for current waveform character (including sub-transient and transient states) and the carried energy, to show the problems with the fuses and MCB usage, to protect circuits in installations fed in a hybrid way (from the grid and synchronous generator set). Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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16 pages, 3300 KiB

Open AccessArticle

Model Predictive Control for Virtual Synchronous Generator with Improved Vector Selection and Reconstructed Current

by Nan Jin, Chao Pan, Yanyan Li, Shiyang Hu and Jie Fang

Energies 2020, 13(20), 5435; https://doi.org/10.3390/en13205435 - 18 Oct 2020

Cited by 13 | Viewed by 2190

Abstract

Due to the large-scale renewable energy connected to the power grid by power electronic converters, the inertia and stability of the power grid is declining. In order to improve the inertia and support the grid recovery, the three-phase converter works as a virtual synchronous generator (VSG) to respond to the frequency and voltage changes of the power grid. This paper proposes a model predictive control for the virtual synchronous generator (MPC-VSG) strategy, which can automatically control the converter output power with the grid frequency and voltage changes. Further consideration of fault-tolerant ability and reliability, the method based on improved voltage vector selection, and reconstructed current is used for MPC-VSG to ensure continuous operation for three-phase converters that have current-sensor faults, and improve the reconstruction precision. The proposed method can respond to the frequency and voltage changes of the power grid and has fault-tolerant ability, which is easy to realize without pulse width modulation (PWM) and a proportional-integral (PI) controller. The effectiveness of the proposed control strategy is verified by experiment. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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20 pages, 5339 KiB

Open AccessArticle

Model Based Optimisation Algorithm for Maximum Power Point Tracking in Photovoltaic Panels

by Faiçal Hamidi, Severus Constantin Olteanu, Dumitru Popescu, Houssem Jerbi, Ingrid Dincă, Sondess Ben Aoun and Rabeh Abbassi

Energies 2020, 13(18), 4798; https://doi.org/10.3390/en13184798 - 14 Sep 2020

Cited by 9 | Viewed by 2095

Abstract

Extracting maximum energy from photovoltaic (PV) systems at varying conditions is crucial. It represents a problem that is being addressed by researchers who are using several techniques to obtain optimal outcomes in real-life scenarios. Among the many techniques, Maximum Power Point Tracking (MPPT) is one category that is not extensively researched upon. MPPT uses mathematical models to achieve gradient optimisation in the context of PV panels. This study proposes an enhanced maximisation problem based on gradient optimisation techniques to achieve better performance. In the context of MPPT in photovoltaic panels, an equality restriction applies, which is solved by employing the Dual Lagrangian expression. Considering this dual problem and its mathematical form, the Nesterov Accelerated Gradient (NAG) framework is used. Additionally, since it is challenging to ascertain the step size, its approximate value is taken using the Adadelta approach. A basic MPPT framework, along with a DC-to-DC convertor, was simulated to validate the results. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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18 pages, 24614 KiB

Open AccessArticle

Testing System for the On-Site Checking of Magneto-Thermal Switches with Arc Fault Detection

by Giovanni Bucci, Fabrizio Ciancetta, Andrea Fioravanti, Edoardo Fiorucci, Simone Mari and Alberto Prudenzi

Energies 2020, 13(18), 4652; https://doi.org/10.3390/en13184652 - 07 Sep 2020

Cited by 9 | Viewed by 2476

Abstract

Arcing is a harmful condition that can lead to electrical fires. The U.S. National Electrical Code requires the installation of electric arc breakers in all residential areas. However, such devices can fail, and therefore, may not work when needed. At present, there are no tests to confirm the correct operation of this type of device. This study aimed to propose an experimental test method to verify the proper functioning of magneto-thermal switches with an electric arc protection function for the occurrence of arc faults. The results show that the proposed method adequately detected the correct operations and tripping time by using different surge suppressors. The proposed system lays the foundations for a portable test system for the periodic checking of electrical systems in which arc fault detection devices (AFDDs) are installed. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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17 pages, 2432 KiB

Open AccessArticle

Density Difference Grid Design in a Point-Mass Filter

by Jakub Matoušek, Jindřich Duník and Ondřej Straka

Energies 2020, 13(16), 4080; https://doi.org/10.3390/en13164080 - 06 Aug 2020

Cited by 6 | Viewed by 1853

Abstract

The paper deals with the Bayesian state estimation of nonlinear stochastic dynamic systems. The stress is laid on the point-mass filter, solving the Bayesian recursive relations for the state estimate conditional density computation using the deterministic grid-based numerical integration method. In particular, the grid design is discussed and the novel density difference grid is proposed. The proposed grid design covers such regions of the state-space where the conditional density is significantly spatially varying, by the dense grid. In other regions, a sparse grid is used to keep the computational complexity low. The proposed grid design is thoroughly discussed, analyzed, and illustrated in a numerical study. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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24 pages, 742 KiB

Open AccessArticle

An Efficient Robust Predictive Control of Main Steam Temperature of Coal-Fired Power Plant

by Di Wang, Xiao Wu and Jiong Shen

Energies 2020, 13(15), 3775; https://doi.org/10.3390/en13153775 - 23 Jul 2020

Cited by 7 | Viewed by 2574

Abstract

Regulating performance of the main steam temperature (MST) system concerns the economy and safety of the coal-fired power plant (CFPP). This paper develops an offset-free offline robust model predictive control (RMPC) strategy for the MST system of CFPP. Zonotope-type uncertain model is utilized as the prediction model in the proposed RMPC design owing to its features of higher accuracy, compactness of representation and less complexity. An offline RMPC aiming at the system robustness and computational efficiency is then developed to maintain the desired steam temperature in case of wide operating condition change. The proposed RMPC is realized by two stages: in the first stage, the RMPC law set, which is the piecewise affine (PWA) of the MST system state is designed offline; then in the second stage, the explicit control law is selected online according to the current state. To achieve an offset-free tracking performance, a manipulated variable target observer is employed to update the chosen RMPC law. The control simulations using on-site operating data of a 1000 MW ultra-supercritical power plant show that the proposed approach can achieve satisfactory control performance and online computation efficiency even under complicated operating conditions. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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15 pages, 2058 KiB

Open AccessArticle

Advanced Control for Hydrogen Pyrolysis Installations

by Dumitru Popescu, Catalin Dimon, Pierre Borne, Severus Constantin Olteanu and Mihaela Ancuta Mone

Energies 2020, 13(12), 3270; https://doi.org/10.3390/en13123270 - 24 Jun 2020

Cited by 2 | Viewed by 1900

Abstract

Today, hydrogen production plays an important part in the industry due to the increasing use of hydrogen in significant domains, such as chemistry, transportation, or energy. In this paper, we aim to design a numerical control solution based on the thermodynamic analysis of the pyrolysis reactions for hydrogen production and to present novel research developments that highlight industrial applications. Beginning with the evaluation of the technological aspects for the pyrolysis chemical process, the paper studies the thermodynamic evaluation of the system equilibrium for the pyrolysis reactions set, to recommend an appropriate automatic control solution for hydrogen pyrolysis installations. The numerical control architecture is organized on two levels, a control level dedicated to key technological parameters, and a supervisory decision level for optimizing the conversion performances of the pyrolysis process. The data employed for modelling, identification, control, and optimization tasks, were obtained from an experimental platform. The scientific results can be implemented on dedicated equipment, to achieve an optimal exploitation of the industrial pyrolysis process. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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13 pages, 4512 KiB

Open AccessArticle

Doubly Fed Induction Generator Open Stator Synchronized Control during Unbalanced Grid Voltage Condition

by Akrama Khan, Xiao Ming Hu, Mohamed Azeem Khan and Paul Barendse

Energies 2020, 13(12), 3155; https://doi.org/10.3390/en13123155 - 18 Jun 2020

Cited by 10 | Viewed by 2291

Abstract

In this paper, a systematic synchronization procedure is proposed for a doubly fed induction generator (DFIG) during unbalanced grid voltage conditions. The initial induced voltage at the open stator terminal is required to synchronize with the grid voltage in magnitude, frequency and phase. An open stator negative sequence rotor current controller is implemented with the conventional DFIG vector controller, which allows the induced stator voltage to become as unbalanced as the grid voltage, hence enabling a smooth connection. A brief comparison is provided for practical issues such as controller structure variation between DFIG open stator and normal operating conditions, and initial encoder rotor angle measurement offset. The procedure is validated experimentally on a 2.2 kW laboratory-scaled DFIG test bench. Full article

(This article belongs to the Special Issue Advanced Control Design and Fault Diagnosis)

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