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A special issue of Automation (ISSN 2673-4052).

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 47335

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Prof. Dr. Eyad H. Abed

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Department of Electrical and Computer Engineering and the Institute for Systems Research, University of Maryland, College Park, MD 20742, USA
Interests: system and control theory; electric power system dynamics and control; systems engineering; the analysis and design of complex networks; communication networks; social networks; aerospace control systems
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Special Issue Information

Dear Colleagues,

As the Editor-in-Chief of Automation, I am pleased to announce the launch of the Special Issue entitled "Anniversary Feature Papers—2022." This Special Issue will be a collection of articles from Editorial Board Members and leading researchers, which will report on new research and cutting-edge developments in the science and engineering of automation and control systems.

Based on the responses of our Editorial Board Members to an initial survey regarding possible topics, the Special Issue will welcome submissions pertaining to the following topics (below, “automation” also includes control and monitoring, related modeling and simulation issues, and other related subjects):

Automation in vehicle networks and systems (land, marine, space and/or air vehicles);
Automation in energy systems;
Automation in learning systems and applications;
Automation in cyberphysical systems.

Our survey received a great response from our Editorial Board Members; however, we request that you do your best to prepare papers for this Special Issue within the set timeframe. Depending on the number of papers received and accepted, the Special Issue may be divided into several issues in the journal, classified by technical area. You are welcome to send a preliminary title and abstract to our Editorial Office ([email protected]) for evaluation. Alternatively, you are welcome to submit full papers of your recent research outcomes if they are within the scope of Automation. All contributions will be peer reviewed.

Prof. Dr. Eyad H. Abed
Guest Editor

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. Automation is an international peer-reviewed open access quarterly 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 1000 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.

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Published Papers (10 papers)

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Research

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16 pages, 1567 KiB

Open AccessArticle

A Semi-Automated Workflow for LULC Mapping via Sentinel-2 Data Cubes and Spectral Indices

by Michel E. D. Chaves, Anderson R. Soares, Guilherme A. V. Mataveli, Alber H. Sánchez and Ieda D. Sanches

Automation 2023, 4(1), 94-109; https://doi.org/10.3390/automation4010007 - 23 Feb 2023

Cited by 6 | Viewed by 3338

Abstract

Land use and land cover (LULC) mapping initiatives are essential to support decision making related to the implementation of different policies. There is a need for timely and accurate LULC maps. However, building them is challenging. LULC changes affect natural areas and local biodiversity. When they cause landscape fragmentation, the mapping and monitoring of changes are affected. Due to this situation, improving the efforts for LULC mapping and monitoring in fragmented biomes and ecosystems is crucial, and the adequate separability of classes is a key factor in this process. We believe that combining multidimensional Earth observation (EO) data cubes and spectral vegetation indices (VIs) derived from the red edge, near-infrared, and shortwave infrared bands provided by the Sentinel-2/MultiSpectral Instrument (S2/MSI) mission reduces uncertainties in area estimation, leading toward more automated mappings. Here, we present a low-cost semi-automated classification scheme created to identify croplands, pasturelands, natural grasslands, and shrublands from EO data cubes and the Surface Reflectance to Vegetation Indexes (sr2vgi) tool to automate spectral index calculation, with both produced in the scope of the Brazil Data Cube (BDC) project. We used this combination of data and tools to improve LULC mapping in the Brazilian Cerrado biome during the 2018–2019 crop season. The overall accuracy (OA) of our results is

88 %

, indicating the potential of the proposed approach to provide timely and accurate LULC mapping from the detection of different vegetation patterns in time series. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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16 pages, 6480 KiB

Open AccessArticle

Automation of a PCB Reflow Oven for Industry 4.0

by Isaí Vilches, Félix Juárez Durán, Alfonso Gómez-Espinosa, Mary Carmen García Carrillo and Jesús Arturo Escobedo Cabello

Automation 2023, 4(1), 78-93; https://doi.org/10.3390/automation4010006 - 15 Feb 2023

Viewed by 4233

Abstract

With the rise of Industry 4.0, its pillars (which include Internet of Things, “Big Data”, data analytics, augmented reality, cybersecurity, etc.) have become unavoidable tendencies for the automated manufacturing industry. Equipment upgrade is required to match the new standards of digitally assisted automation. However, not all factories in the medium to small range (or independent manufacturers) can afford to upgrade their equipment. Therefore, the availability of affordable Industry 4.0 upgrades for now-outdated devices is necessary for manufacturers in the SME range (Small-Medium Enterprises) to stay relevant and profitable. More specifically, this work revolves around the automation of printed circuit board (PCB) manufacturing, which is one of the most popular and profitable areas involved in this movement; and within it, the large majority of manufacturing defects can be traced to the soldering or “reflow” stage. Manufacturing research must, thus, aim towards improving reflow ovens and, more specifically, aim to improve their autonomous capabilities and affordability. This work presents the design and results of a controlling interface utilizing a Raspberry Pi 4 as a coupling interface between an MQTT Broker (which monitors the overall system) and the oven itself (which is, intentionally, a sub-prime model which lacks native IoT support), resulting in successful, remote, network-based controlling and monitoring of the oven. Additionally, it documents the design and implementation of the network adaptations necessary for it to be considered a cybersecure IIoT Module and connect safely to the Production Cell’s Subnet. All of this to address the inclusion of specific Industry 4.0 needs such as autonomous functioning, data collection and cybersecurity in outdated manufacturing devices and help enrich the processes of SME PCB manufacturers. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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21 pages, 660 KiB

Open AccessArticle

Evaluation of the Regions of Attraction of Higher-Dimensional Hyperbolic Systems Using Extended Dynamic Mode Decomposition

by Camilo Garcia-Tenorio, Duvan Tellez-Castro, Eduardo Mojica-Nava and Alain Vande Wouwer

Automation 2023, 4(1), 57-77; https://doi.org/10.3390/automation4010005 - 4 Feb 2023

Cited by 1 | Viewed by 2126

Abstract

This paper provides the theoretical foundation for the approximation of the regions of attraction in hyperbolic and polynomial systems based on the eigenfunctions deduced from the data-driven approximation of the Koopman operator. In addition, it shows that the same method is suitable for analyzing higher-dimensional systems in which the state space dimension is greater than three. The approximation of the Koopman operator is based on extended dynamic mode decomposition, and the method relies solely on this approximation to find and analyze the system’s fixed points. In other words, knowledge of the model differential equations or their linearization is not necessary for this analysis. The reliability of this approach is demonstrated through two examples of dynamical systems, e.g., a population model in which the theoretical boundary is known, and a higher-dimensional chemical reaction system constituting an original result. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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13 pages, 14581 KiB

Open AccessArticle

Fast and Precise Generic Model for Position-Based Trajectory Prediction of Inland Waterway Vessels

by Navreet S. Thind, Justus Hering and Dirk Söffker

Automation 2022, 3(4), 633-645; https://doi.org/10.3390/automation3040032 - 30 Nov 2022

Viewed by 2340

Abstract

Vessel motion simulation as well as model-based accurate trajectory prediction of vessels require accurate models with respect to related dynamic properties. The ability to predict vessel’s trajectory behaviors will become relevant in the case of future autonomous navigation of vessels to predict the behavior of others. The definition of models or parameters can be realized via first principles or by using experimental modeling methods leading to a time invariant or variant model. Existing hydrodynamical modeling approaches are based on mathematical approaches, which use parameters like mass, hydrodynamic forces, wind velocity, depth under the keel, loading parameters, etc. So, determining a dynamic vessel’s model is a complex task, since the model is vessel-specific. For collision avoidance of autonomous or assisted vessels, the trajectory prediction of encountering other vessels is especially required. It is not possible to use complex hydrodynamical models of encountering vessels online due to missing required information/measurements. Even existing deep learning approaches provide better predictions, but are still insufficient for collision avoidance in the case of strong dynamical changes, since the considered input sequences are long. Due to long input sequences, the model does not adapt to strong dynamical changes. In this work, a simple parameter-based approach is developed to predict the intended behavior using the last seconds of the measured position variables. The idea is to globally identify the model parameters of the vessel, which remains constant for the situation, and additionally two parameters for local adaptation, which adapt at every updated input sequence. Typically parameters like rudder angle, wind velocities, and water current affect the behavior of vessels. The introduced approach works with a sliding window approach for which, after identification of the global system, local values are identified based on the last 80 measurements of the vessels. A trajectory prediction (assuming no additional rudder-based maneuvering) is realized for the prediction horizon of 180 s. To confirm the robustness of the new approach, real AIS/GPS-based measurements from a German research inland vessel for different scenarios and sailing conditions including ‘loaded’ and ‘empty’ sailing cases are used. Furthermore, additional results are shown for position data information of different sample rates. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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11 pages, 19911 KiB

Open AccessArticle

Detection of Hand Poses with a Single-Channel Optical Fiber Force Myography Sensor: A Proof-of-Concept Study

by Matheus K. Gomes, Willian H. A. da Silva, Antonio Ribas Neto, Julio Fajardo, Eric Rohmer and Eric Fujiwara

Automation 2022, 3(4), 622-632; https://doi.org/10.3390/automation3040031 - 18 Nov 2022

Cited by 1 | Viewed by 2616

Abstract

Force myography (FMG) detects hand gestures based on muscular contractions, featuring as an alternative to surface electromyography. However, typical FMG systems rely on spatially-distributed arrays of force-sensing resistors to resolve ambiguities. The aim of this proof-of-concept study is to develop a method for identifying hand poses from the static and dynamic components of FMG waveforms based on a compact, single-channel optical fiber sensor. As the user performs a gesture, a micro-bending transducer positioned on the belly of the forearm muscles registers the dynamic optical signals resulting from the exerted forces. A Raspberry Pi 3 minicomputer performs data acquisition and processing. Then, convolutional neural networks correlate the FMG waveforms with the target postures, yielding a classification accuracy of (93.98 ± 1.54)% for eight postures, based on the interrogation of a single fiber transducer. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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15 pages, 3879 KiB

Open AccessArticle

Model-Based Firmware Generation for Acquisition Systems Using Heterogeneous Hardware

by Rens Baeyens, Joachim Denil, Jan Steckel and Walter Daems

Automation 2022, 3(3), 471-485; https://doi.org/10.3390/automation3030024 - 15 Aug 2022

Cited by 2 | Viewed by 3071

Abstract

High-performance sensing and control systems have an important role in Industry 4.0. However, with the current solutions, the development effort is high and requires specialized skills in electronic engineering. Therefore, a model-based approach on control and signal processing systems using affordable heterogeneous hardware is proposed. In this work, a model-based code generator is developed to abstract the user from the actual software implementation. Starting from a combined model of a timing diagram and an embedded platform, a model transformation is used to automatically generate functional acquisition firmware. This firmware generator enables system engineers without deep software and hardware knowledge to set up complex control systems. Furthermore, it equips software engineers with a solid framework for faster development. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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13 pages, 7503 KiB

Open AccessArticle

WildTrack: An IoT System for Tracking Passive-RFID Microchipped Wildlife for Ecology Research

by Robert Ross, Ben Anderson, Brian Bienvenu, Emily L. Scicluna and Kylie A. Robert

Automation 2022, 3(3), 426-438; https://doi.org/10.3390/automation3030022 - 8 Aug 2022

Cited by 7 | Viewed by 5041

Abstract

Wildlife tracking is used to acquire information on the movement, behaviour and survival of animals in their natural habitat for a wide range of ecological questions. However, tracking and monitoring free-ranging animals in the field is typically labour-intensive and particularly difficult in species that are small, cryptic, or hard to re-capture. In this paper, we describe and evaluate an Internet-of-Things (IoT)-based tracking system which automatically logs detected passive RFID tags and uploads them to the cloud. This system was successfully evaluated with 90 sensor modules deployed in a 30 ha wildlife sanctuary to monitor a small nocturnal mammal of less than 20 g in body size. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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16 pages, 1391 KiB

Open AccessArticle

Toward More Realistic Social Distancing Policies via Advanced Feedback Control

by Cédric Join, Alberto d’Onofrio and Michel Fliess

Automation 2022, 3(2), 286-301; https://doi.org/10.3390/automation3020015 - 9 Jun 2022

Cited by 4 | Viewed by 2804

Abstract

A continuously time-varying transmission rate is suggested by many control-theoretic investigations on non-pharmaceutical interventions for mitigating the COVID-19 pandemic. However, such a continuously varying rate is impossible to implement in any human society. Here, we significantly extend a preliminary work (M. Fliess, C. Join, A. d’Onofrio, Feedback control of social distancing for COVID-19 via elementary formulae, MATHMOD, Vienna, 2022), based on the combination of flatness-based and model-free controls with respect to the classic parsimonious SIR model. Indeed, to take into account severe uncertainties and perturbations, we propose a feedback control where the transmission rate, i.e., the control variable, is piecewise constant. More precisely, the transmission rate remains constant during an appreciable time interval, which is not too large. Strict extended lockdowns may therefore be avoided. The poor knowledge of fundamental quantities such as the rate of infection hinders a precise calibration of the transmission rate. Thus, the results of our approach ought therefore not to be regarded as rules of action to follow accurately but as a guideline for a wise behaviour. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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Review

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34 pages, 1150 KiB

Open AccessReview

Modeling and Control of Satellite Formations: A Survey

by Boris Andrievsky, Alexander M. Popov, Ilya Kostin and Julia Fadeeva

Automation 2022, 3(3), 511-544; https://doi.org/10.3390/automation3030026 - 19 Sep 2022

Cited by 15 | Viewed by 5188

Abstract

This survey deals with the problem of the group motion of spacecraft, which is rapidly developing and relevant for many applications, in terms of developing the onboard control algorithms to ensure the fulfillment of a given mission. The paper provides a comprehensive overview of spacecraft formation flight control. The bibliography is divided into three main sections: the multiple-input–multiple-output approach, in which the formation is treated as a single entity with multiple inputs and multiple outputs; the leader–follower formation, in which individual spacecraft controllers are linked hierarchically; and a virtual structure formation, in which spacecraft are treated as rigid bodies embedded in a common virtual rigid body. This survey expands a 2004 survey and updates it with recent results. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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25 pages, 8946 KiB

Open AccessReview

A Tutorial and Review on Flight Control Co-Simulation Using Matlab/Simulink and Flight Simulators

by Nadjim Horri and Mikolaj Pietraszko

Automation 2022, 3(3), 486-510; https://doi.org/10.3390/automation3030025 - 3 Sep 2022

Cited by 20 | Viewed by 14816

Abstract

Flight testing in a realistic three-dimensional virtual environment is increasingly being considered a safe and cost-effective way of evaluating aircraft models and their control systems. The paper starts by reviewing and comparing the most popular personal computer-based flight simulators that have been successfully interfaced to date with the MathWorks software. This co-simulation approach allows combining the strengths of Matlab toolboxes for functions including navigation, control, and sensor modeling with the advanced simulation and scene rendering capabilities of dedicated flight simulation software. This approach can then be used to validate aircraft models, control algorithms, flight handling chatacteristics, or perform model identification from flight data. There is, however, a lack of sufficiently detailed step-by-step flight co-simulation tutorials, and there have also been few attempts to evaluate more than one flight co-simulation approach at a time. We, therefore, demonstrate our own step-by-step co-simulation implementations using Simulink with three different flight simulators: Xplane, FlightGear, and Alphalink’s virtual flight test environment (VFTE). All three co-simulations employ a real-time user datagram protocol (UDP) for data communication, and each approach has advantages depending on the aircraft type. In the case of a Cessna-172 general aviation aircraft, a Simulink co-simulation with Xplane demonstrates successful virtual flight tests with accurate simultaneous tracking of altitude and speed reference changes while maintaining roll stability under arbitrary wind conditions that present challenges in the single propeller Cessna. For a medium endurance Rascal-110 unmanned aerial vehicle (UAV), Simulink is interfaced with FlightGear and with QGroundControl using the MAVlink protocol, which allows to accurately follow the lateral UAV path on a map, and this setup is used to evaluate the validity of Matlab-based six degrees of freedom UAV models. For a smaller ZOHD Nano Talon miniature aerial vehicle (MAV), Simulink is interfaced with the VFTE, which was specifically designed for this MAV, and with QGroundControl for the testing of advanced H-infinity observer-based autopilots using a software-in-the-loop (SIL) simulation to achieve robust low altitude flight under windy conditions. This is then finally extended to hardware-in-the-loop (HIL) implementation on the Nano Talon MAV using a controller area network (CAN) databus and a Pixhawk-4 mini autopilot with simulated sensor models. Full article

(This article belongs to the Special Issue Anniversary Feature Papers-2022)

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