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Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVI Conference 2024

作者： Ho, Ming-Han Yan, Yung-Jhe Cheng, Yu-Cheng Chou, Cong Yuan Ou-Yang, Mang Graduate Degree Program of Artificial Intelligence National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Intelligent Systems National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Smart Industry and Green Energy National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781510680906

Hyperspectral imaging is beneficial for non-destructive agricultural inspections, and three-dimensional reconstruction modeling is a powerful tool for inspecting the phenotype of plants. This study proposes an approach to combine three-dimensional reconstruction modeling and hyperspectral images into four-dimensional data. This data not only contains the three-dimensional structural information of an interesting object but also includes the spectral information of every point on the surface of this object. Firstly, the hyperspectral and visible images of an interesting object are acquired from hyperspectral and visible cameras. Secondly, high-resolution visible images are used to reconstruct a three-dimensional surface model of an interesting object. Thirdly, matching hyperspectral images with visible images establishes the correspondence between hyperspectral images and the three-dimensional model. Furthermore, the biomarker index can be derived from hyperspectral data. The biomarker index can be transformed into surface textures and combined with the three-dimensional model to form a three-dimensional biomarker model. © 2024 SPIE.

关键词： Hyperspectral imaging

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Model Predictive control of a Hybrid VA v for Parcel Delivery Applications 1

Model Predictive Control of a Hybrid VA v for Parcel Deliver...

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1st AIRPHARO Workshop on Aerial Robotic systems Physically Interacting with the Environment, AIRPHARO 2021

作者： Konyalioglu, Turan Alnipak, Sinan Altug, Erdinc İstanbul Technical University System Dynamics and Control Graduate Program İstanbul Technical University Autonomous Systems Research Laboratory Department of Mechanical Engineering İstanbul Turkey

ISBN: (纸本)9781665433891

Within the last decade, e-commerce has increased at an extraordinary level. The widespread use of Unmanned Aerial Vehicles (VAVs) in the logistics sector can reduce traffic density, improve delivery time, and can provide contactless delivery. This work proposes a new hybrid VAV, that combines the benefits of vertical take-off and land vehicle and a fixed-wing aircraft. It can carry multiple packages, which can decent automatically towards the recipients. This approach eliminates time-consuming landing maneuvers of the VA V for delivery. This work focuses on the design of the vehicle, and the challenges of the transitions from VTOL to aircraft modes and vice versa with a Model Predictive controller. © 2021 IEEE.

关键词： Fixed wings

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Relationship Between Mechanical Deformation and Contact Force Applied by Catheter Tip on Cardiac Muscle: Experimentation and Computer Modeling

Relationship Between Mechanical Deformation and Contact Forc...

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IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability (ECBIOS)

作者： Yukako Ijima Kriengsak Masnok Juan J. Perez Ana González-Suárez Enrique Berjano Nobuo Watanabe Master's Program Global Course of Engineering and Science Graduate School of Engineering and Science Shibaura Institute of Technology Saitama Japan Biofluid Science and Engineering Laboratory Functional Control Systems Graduate School of Engineering and Science Shibaura Institute of Technology Saitama Japan Department of Electronic Engineering BioMIT Universitat Politecnica de Valencia Valencia Spain Translational Medical Device Lab School of Engineering University of Galway Galway Ireland Department of Bio-Science and Engineering Biofluid Science and Engineering Laboratory Functional Control Systems Graduate School of Engineering and Science College of Systems Engineering and Science Shibaura Institute of Technology Saitama Japan

The cardiac muscle is elastic and deformable. Pushing a catheter in contact with the cardiac muscle surface to conduct focal energy-based ablative therapies, such as RF ablation, requires an adequate electrode-tissue contact surface to transfer the energy to the target site. In this regard, the relationship between the contact force (CF) and the resulting mechanical response is still unclear, in particular, the insertion depth (ID) and the diameter of the surface deformation. The objective of this study was to quantify these relationships using an ex vivo model and a computational model. A rigid bar with a 2.3 mm diameter blunt tip (mimicking a 7Fr standard ablation catheter) was placed at a perpendicular orientation on a fragment of the porcine heart. CF values ranged from 10 to 80g. We used ANSYS to build a Mooney-Rivlig model of 3 parameters based on hyperelastic material and to simulate the same conditions as in the experiments. The experimental results showed a strong linear correlation between CF and insertion depth ID ( $\mathrm{R}^{2}=0.97, \mathrm{P} < 0.001$ ), from $0.7 \pm 0.3$ mm at 10 gto $6.9 \pm 0.1$ mm at 80 g. We also found a strong linear correlation between CF and minor and major diameters of the surface deformation assessed, from $4.0 \pm 0.4$ mm at 20 g to $10.3 \pm 0.0$ mm at 80 g ( $\mathrm{R}^{2}=0.96$ ), and from $6.4 \pm 0.7$ mm at 20 g to $16.7 \pm 0.1$ mm at 80 g ( $\mathrm{R}^{2}=0.95$ ), respectively. A descent gradient algorithm was used to minimize the mean square error (MSE) between the experimental and computational results of ID for the 10 values of CF. After trying different combinations for the3 parameters of the Mooney-Rivlig model, an optimal fit was achieved after 5 iterations, with an error of less than 0.55 mm for ID. This same mode was then used to predict the diameter of the surface deformation, obtaining an error of less than 0.65 mm. The results confirm that a Mooney-Rivlig model of three parameters based on

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Multi-objective Machine Learning for control performance assessment in PID control loops ⁎

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IFAC-PapersOnLine 2024年第7期58卷 168-173页

作者： Gilberto Reynoso-Meza Jesús Carrillo-Ahumada Tainara Marques Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifícia Universidade Católica do Paraná (PUCPR) Rua Imaculada Conceição 1155 Curitiba Brazil Control Systems Optimization Laboratory (LOSC) Pontifícia Universidade Católica do Paraná (PUCPR) Ingeniería en Alimentos. Universidad del Papaloapan. Circuito Central 200 Col. Parque Industrial 68301 Tuxtepec Oaxaca Mex

control Performance Assessment (CPA) is a critical endeavor in industrial processes, ensuring optimal functioning of control systems. Traditionally, CPA has been addressed through solutions using some control performance indicators. Nowadays, the integration of data science and machine learning has emerged as a viable alternative, particularly in classification tasks related to CPA. That is, in a binary classification scheme, the goal is to predict whether incoming data from the control loop belongs to class 0 or 1, representing the absence or presence of an anomaly (performance degradation). In such a case, a trade-of between false positives and false negatives should be obtained, via the training phase of a given supervised machine learning structure for example. Usually, this is a conflicting trade-of, where multi-objective optimization techniques in the training phase of such learners could bring interesting results. In this paper, we explore the usability of multi-objective optimization training in machine learning, for control performance assessment classification. A database describing 30 control performance indicators (features) in a PID control loop is used. The obtained results indicate that the proposed approach could bring interesting applications to improve the performance of CPA classification systems.

关键词： control performance assessment machine learning multi-objective optimization PID control multi-criteria analysis

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Towards Real-Time Machining Tool Failure Forecast Approach for Smart Manufacturing systems

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IFAC-PapersOnLine 2022年第2期55卷 548-553页

作者： Nicolas Nebelung Mario D.S. de Oliveira Santos Sofia T. Helena Athon F.C.S. de Moura Leite Matheus B. Canciglieri Anderson L. Szejka Control and Automation Engineering Department Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil Junior Scientific Initiation Program at the Nossa Senhora de Medianeira School and Pontifical Catholic University of Paraná Curitiba – Paraná Brazil Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Curitiba Brazil

Industry 4.0 is characterized by a dynamic market that constantly looking for new methods to optimize and integrate manufacturing processes. In this context, Artificial Intelligence has gained prominence in problem-solving, such as failure prediction and decision making, thus improving product quality, and consequently bringing competitiveness to the company. Aiming to contribute to this scenario, this research develops a data treatment system that, from an intelligent tool and an interoperable ontological model, automates the prediction and detection of failures in machining machines lines. The system was developed for the prediction of faults in machining lines includes an artificial intelligence formed from prediction algorithms and inferences, it is possible to guarantee the correct treatment and communication of data at different stages of the process. For the experimental research, was used data collected from a machining line of a public dataset. The information is collected and classified by Artificial Intelligence that supports a decision system. The prediction of tool wear would enable the system to infer the type of problem that is causing this wear, a possible root cause, and the needed maintenance based on the ontological inference tool. By this classification of data, it is possible to achieve, through inferences, a reduction in the decision scope, bringing the possible problems caused by the incoming value. The semantic interoperability ensures correct data exchange and processing, which generates a more assertive view of production failures. The system may help companies to increase their productive process by helping them identify future failures in production if applied in a real scenario.

关键词： Industry 4.0 Smart System Artificial Intelligence Machine Learning Ontology Machine Failure Forecast

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Adaptive control Applied to Half-Bridge Synchronous Buck Converter using LCL Filter for Charging Batteries

Adaptive Control Applied to Half-Bridge Synchronous Buck Con...

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Power Electronics and control (SEPOC), Seminar on

作者： Vinícius Descovi Rodrigues João Vitor Merlo Jonas Roberto Tibola Rodrigo Varella Tambara Research and Development Center in Electrical Engineering - NUPEDEE Federal University of Santa Maria Santa Maria Brasil Graduate Program in Electrical Engineering - PPGEE Federal University of Santa Maria Santa Maria Brasil Research and Development Center in Electrical and Computational Systems - GSEC Federal University of Santa Maria Santa Maria Brasil Group of Power Electronics and Control - GEPOC Federal University of Santa Maria Santa Maria Brasil

ISBN: (数字)9798350379419

ISBN: (纸本)9798350379426

This paper proposes a discrete-time Model Reference Adaptive controller (MRAC), applied to a Half-Bridge synchronous buck converter for charging batteries. The system uses an LCL filter that interfaces the power converter and the batteries. A virtual plant method is proposed for better transitory response of the adaptive control system. The model reference utilizes a reduced order, to simplify the project of the adaptive controller. Simulation results are presented for validation of the control project.

关键词： Seminars Adaptation models Buck converters Simulation Power electronics Batteries Topology Adaptive control

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Real engineering Problems in an Undergraduate Course: The learning methodologies and assessment tools

Real Engineering Problems in an Undergraduate Course: The le...

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World engineering Education Forum - Global engineering Deans Council (WEEF-GEDC)

作者： Ricardo A. Diogo André L.A.C. Venâncio Maria Angela M. Roveredo Santos Eduardo F.R. Loures Neri dos Santos Knowledge Engineering&Management Graduate Program Federal University of Santa Catarina Florianopolis Brazil Industrial&Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Control and Automation Engineering/Mechatronics Engineering Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9781665424899

This paper presents the context of the Ubiquitous Computing course carried out in an Industrial engineering undergraduate program throughout 2020 and the first semester of 2021. This course took advantage of the Institutional Modernization program led by the control and Automation engineering Undergraduate program, which consists in the modernization of undergraduate engineering programs at the Pontifical Catholic University of Paraná. The course aimed to help develop competencies, i.e., a set of knowledge, skills, and attributes aligned with Student Outcomes suggested by ABET. Also, the course proposal brought the productive sector very close to the academic environment, proposing real engineering problems as challenges. However, what are the methods and assessment tools for practical learning in a course with modern elements? This paper proposed the flipped learning and the Challenge-Based Learning Framework with the support of the CDIO Framework as learning methodologies to answer such question. Additionally, quizzes, tests, presentations, rubrics, and peer evaluation were applied as assessment tools to measure the student's progress. Finally, students were listened to about their perceptions during the course. The results suggested that the learning methodologies and assessment tools are suitable for the course context, although some improvements are expected for the following course offers. Moreover, students approved the initiative to bring in real challenges proposed by companies, the mentoring hours, and the feedback about the projects.

关键词： Automation Companies Industrial engineering Ubiquitous computing Proposals Mentoring engineering education

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AImotion Challenge Results: a Framework for AirSim Autonomous Vehicles and Motion Replication

AImotion Challenge Results: a Framework for AirSim Autonomou...

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Computers and Automation (CompAuto), International Conference on

作者： Bruno J. Souza Lucas C. de Assis Dominik Rößle Roberto Z. Freire Daniel Cremers Torsten Schön Munir Georges Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil Control and Automation Eng. Department Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil Technische Hochschule Ingolstadt AImotion Bavaria Institute Ingolstadt Germany Department of Informatics Technical University of Munich Munich Germany

ISBN: (纸本)9781665481953

The use of simulation environments is becoming more significant in the development of autonomous cars, as it allows for the simulation of high-risk situations while also being less expensive. In this paper, we presented a framework that allows the creation of an autonomous vehicle in the AirSim simulation environment and then transporting the simulated movements to the TurtleBot. To maintain the car in the correct direction, computer vision techniques such as object detection and lane detection were assumed. The vehicle's speed and steering are both determined by Proportional-Integral-Derivative (PID) controllers. A virtual personal assistant was developed employing natural language processing to allow the user to interact with the environment, providing movement instructions related to the vehicle's direction. Additionally, the conversion of the simulator movements for a robot was implemented to test the proposed system in a practical experiment. A comparison between the real position of the robot and the position of the vehicle in the simulated environment was considered in this study to evaluate the performance of the algorithms.

关键词： Computer vision Lane detection Robot kinematics Atmospheric modeling Computational modeling Virtual environments Natural language processing

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Robust Current control of Three-Phase Grid-Connected Converters by Using the ADRC Method 16

Robust Current Control of Three-Phase Grid-Connected Convert...

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16th Brazilian Power Electronics Conference, COBEP 2021

作者： Campos De Araujo, Diana Alves Moor Neto, Joao Amin Do Brasil, Thiago Americano Gouvea, Josiel Alves Lopes Zachi, Alessandro Rosa Electrical Engineering Graduate Program Centro Fed. de Educ. Tecn. Celso Suckow da Fonseca CEFET/RJ Rio de Janeiro Brazil Centro Fed. de Educ. Tecn. Celso Suckow da Fonseca CEFET/RJ Department of Electrical Engineering Rio de Janeiro Brazil Centro Fed. de Educ. Tecn. Celso Suckow da Fonseca CEFET/RJ Department of Control Systems and Automation Rio de Janeiro Brazil

ISBN: (纸本)9781665421294

This paper addresses the control design of a current mode control for a three-phase voltage source converter. A variant of the Active Disturbance Rejection control (ADRC) scheme is proposed for comparison with the classical inner control approach. The ADRC method has a straightforward design procedure and has well-known abilities for disturbance rejection and robustness to parametric uncertainties of the system. Theoretical studies are presented and simulation results are discussed by using EMTP-RV environment considering the system Synchronous Reference Frame control, whose modeling was extracted from the analysis performed in a classical refer-ence. © 2021 IEEE.

关键词： Electric current control

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Enabling Invariant Models to Describe Time-Varying Dynamics: A Case Study ⁎

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IFAC-PapersOnLine 2021年第14期54卷 1-6页

作者： Petrus E.O.G.B. Abreu Victor D.R. Dreke Luis A. Aguirre Claudio Garcia Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Av. Antônio Carlos 6627 31270-901 Belo Horizonte MG Brazil Control Systems Group Eindhoven University of Technology 5600 MB Eindhhover The Netherlands Department of Telecommunications and Control Engineering Escola Politécnica da Universidade de São Paulo Av. Prof. Luciano Gualberto 158 São Paulo SP Brazil

This work addresses the problem of identifying nonlinear and time-varying behaviors using Nonlinear polynomial AutoRegressive models with eXogenous inputs (NARX). Two approaches are investigated. The first one is based on a recursive algorithm with an adaptive forgetting factor to update the parameters of black-box models. The second approach aims to include a certain class of regressors to identify invariant models, i.e. with constant parameters, to describe such behaviors. An experimental case study of a pH neutralization process is carried out, which indicated the presence of behaviors that resemble varying dynamics features. Time-invariant models with a specific class of regressors are proposed and seem to be a promising way to deal with such dynamics.

关键词： Gray-box identification pH system NARX model varying dynamics

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