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Training Swinging Door Trending Compression Algorithm for IoT devices 10

Training Swinging Door Trending Compression Algorithm for Io...

引用

10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Correa, Juan David Arias Pinto, Alex Sandro Roschildt Montez, Carlos Post-graduate Program of Automation Systems Engineering Florianópolis Brazil Dept. of Informatics and Statistic Dept. of Automation and Systems Engineering Florianópolis Brazil Dept. of Automation and Systems Engineering Florianópolis Brazil

ISBN: (纸本)9798350373011

The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device's resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data Compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the Compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the Compression and Error metrics to evaluate the compression performance in Lossy Algorithms. © 2024 IEEE.

关键词： Data compression ratio

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L2 Input-to-State Stability and Stabilization of Coupled Linear ODE-Hyperbolic PDE systems∗ 63

L2 Input-to-State Stability and Stabilization of Coupled Lin...

引用

63rd IEEE Conference on Decision and Control, CDC 2024

作者： Coutinho, Daniel Andrade, Gustavo Artur De Carvalho, Franthiescolly Vieira De Federal University of Santa Catarina Department of Automation and Systems Engineering Florianópolis88040-370 Brazil Federal University of Santa Catarina Post-graduate Program in Automation and Systems Engineering Florianópolis88040-370 Brazil

ISBN: (纸本)9798350316339

This paper addresses the problem of input-to-state stability (ISS) and stabilization of linear ordinary differential equations (ODEs) coupled with a system of homogeneous linear hyperbolic partial differential equations (PDEs) through the boundaries. First, a Lyapunov result characterizing the ISS property for finite-dimensional systems is extended to deal with coupled ODE and PDE systems. The proposed ISS condition is then applied to derive stability and stabilization conditions in terms of linear matrix inequality constraints assuming magnitude bounded disturbances at the boundaries. Two convex optimization problems are also proposed in order to obtain either an optimized reachable set estimate or a boundary controller that minimizes the disturbance effects on the L2 × R-norm of the system states. Numerical examples illustrate the potential of the proposed approach. © 2024 IEEE.

关键词： Convex optimization

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L2 Input-to-State Stability and Stabilization of Coupled Linear ODE-Hyperbolic PDE systems*

L2 Input-to-State Stability and Stabilization of Coupled Lin...

引用

IEEE Conference on Decision and Control

作者： Daniel Coutinho Gustavo Artur de Andrade Franthiescolly Vieira de Carvalho Department of Automation and Systems Engineering Federal University of Santa Catarina Florianópolis Brazil Post-graduate Program in Automation and Systems Engineering Federal University of Santa Catarina Florianópolis Brazil

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper addresses the problem of input-to-state stability (ISS) and stabilization of linear ordinary differential equations (ODEs) coupled with a system of homogeneous linear hyperbolic partial differential equations (PDEs) through the boundaries. First, a Lyapunov result characterizing the ISS property for finite-dimensional systems is extended to deal with coupled ODE and PDE systems. The proposed ISS condition is then applied to derive stability and stabilization conditions in terms of linear matrix inequality constraints assuming magnitude bounded disturbances at the boundaries. Two convex optimization problems are also proposed in order to obtain either an optimized reachable set estimate or a boundary controller that minimizes the disturbance effects on the ${\mathcal{L}}_{2} \times \mathbb{R}$-norm of the system states. Numerical examples illustrate the potential of the proposed approach.

关键词： Partial differential equations Ordinary differential equations Convex functions Linear matrix inequalities Numerical stability

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Capacitance Estimation Algorithm for Condition Monitoring of Electrolytic DC-Link Capacitors Using Artificial Neural Network in Front-End Diode Rectifier Three-Phase Motor Drive systems

Capacitance Estimation Algorithm for Condition Monitoring of...

引用

IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Mateus Abreu de Andrade Rodolfo César Costa Flesch Graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis Brazil

A factor that must be taken into account in the modern design of power electronics converters is the reliability of dc-link capacitors, but traditional condition monitoring methods require extra hardware that increase the overall cost. This work proposes and experimentally evaluates a condition monitoring method for electrolytic dc-link capacitors in three-phase front-end diode rectifier motor drives which does not require hardware modifications. The presented method uses an artificial neural network (ANN) to predict the capacitance value of the dc-link capacitor bank. Based on time-domain parameters, the ANN is trained and evaluated using an error analysis to determine the effectiveness of the proposed method with a printed circuit board capacitor jig and aged samples. The proposed method is evaluated in several operating conditions and the results show that the prediction errors are less than 2.4% and that the method is able to monitor the degradation level of the dc-link capacitor bank.

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Single Inductor Dual Buck Inverter Classical and Predictive Linear Voltage Controller Comparison 8

Single Inductor Dual Buck Inverter Classical and Predictive ...

引用

8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Patarroyo-Gutierrez, Luis David Nakamoto Yamaguti, Nelson Nayoshi Hernández-Gómez, Oscar Mauricio MacEdo Da Silva, Daniel Abreu School of Electronic Engineering Universidad Pedagógica y Tecnológica de Colombia Tunja Boyacá Colombia Federal University of Santa Catarina Dep. of Automation and Systems SC Florianopolis Brazil Electrical Engineering Graduate Program Federal University of Pará Belem Brazil

ISBN: (纸本)9798350321128

This article presents the mathematical model of a 2 KW DBI (Dual Buck Inverter) converter that can be used in renewable energy applications. The inverter operating modes are described with the equations that model their behavior with the activation signals of the MOSFETs. The switching model is built. Simulation results are presented by applying linear control through a PI controller and GPC (Generalized Predictive Controller) hybridized in PID structure;simulation results are recorded in PSIM © verifying the control response due to changes in the load and the input DC voltage level.

关键词： Automatic Voltage Control Control of Power Electronic systems DC-AC Power Converters Dual Buck Inverter Inverter

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Training Swinging Door Trending Compression Algorithm for IoT devices

Training Swinging Door Trending Compression Algorithm for Io...

引用

IEEE World Forum on Internet of Things (WF-IoT)

作者： Juan David Arias Correa Alex Sandro Roschildt Pinto Carlos Montez Post-graduate Program of Automation Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil Dept. of Informatics and Statistic Dept. of Automation and Systems Engineering Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device’s resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data Compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the Compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the Compression and Error metrics to evaluate the compression performance in Lossy Algorithms.

关键词： Training Performance evaluation Communication systems Data compression Prediction algorithms Market research Internet of Things Computational complexity Compression algorithms

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Hardware Implementation of a Sliding Detection Algorithm for Robotic Hands Using Force Sensors

Hardware Implementation of a Sliding Detection Algorithm for...

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Symposium on Integrated Circuits and systems Design (SBCCI)

作者： Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Systems Graduate Program Automation and Control Group/GRACO Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

In this work, a sliding detection algorithm was proposed for a previously developed robotic hand through the utilization of force sensors. Previous works have designed several hardware architectures to filter sensor data, implement dynamic control, and machine learning models for controlling the robotic fingers using a single Field programmable Gate Arrays (FPGA) chip. In this regard, the slip detection algorithm was developed to comprise three stages, each with a low computational cost, including a moving average filter, a first-order derivative, and a peak detection algorithm. A reference model was constructed and validated through an experimental protocol employing daily use objects to create a database. Subsequently, the slip detection algorithm was mapped onto hardware utilizing previously developed floating-point arithmetic IP cores and implemented using a Zynq 7020 device. The FPGA implementation was characterized in terms of resource occupation, power consumption, execution time, and numerical error with the reference model.

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A preliminary discussion of digital transformation and semantic interoperability to support the information exchange in the business process 28

A preliminary discussion of digital transformation and seman...

引用

28th ISTE International Conference on Transdisciplinary engineering, TE 2021

作者： Nakano, Lucas Yoshio Bertoldi, Pedro Henrique Szejka, Anderson Luis Canciglieri Junior, Osiris Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Automation and Control Engineering Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9781643682082

The development of interoperability is more and more an essential task for all kinds of organizations. It needs to be measured, verified, and continuously improved. With the advent of the Internet of Things, Industry 4.0, Digital Transformation, as well as all technologies it brings, such as big data, cloud computing, and mobile applications, this subject become quite ordinary and necessary, not only in a manufacturing scenario but also in a business process. As crucial benefits, it can bring possible gains for developers and users, also reduce the efforts to communicate multiple and different platforms. Like all new implementations, there are significant challenges that have to be overcome to allow satisfactory results. In this paper, after a systematic literature review to better understand the technologies and this new situation, we conduct a study involving a case in a business process, presenting some actions that can be executed and technologies that can be implemented to reach a well interoperable environment. For instance, to analyze the interoperability maturity level and to adopt ontologies as an alternative to integrate heterogeneous systems. Finally, in the last part of the paper, we give conclusions and perspectives for futures works. © 2021 The authors and IOS Press.

关键词： Interoperability

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Enhancing IoT Intrusion Detection with Federated Learning-Based CNN-GRU and LSTM-GRU Ensembles

Enhancing IoT Intrusion Detection with Federated Learning-Ba...

引用

International Symposium on Wireless Communication systems (ISWCS)

作者： Ogobuchi Daniel Okey Demostenes Zegarra Rodriguez João Henrique Kleinschmidt Center for Engineering Modeling and Applied Social Sciences Federal University of ABC São Paulo Brazil Graduate Program in Systems and Automation Engineering Federal University of Lavras Minas Gerais Brazil

ISBN: (数字)9798350362510

ISBN: (纸本)9798350362527

The Internet of Things (IoT) devices have been identified to have low security measures by default, thus making them highly vulnerable to malicious attacks. Machine learning-based intrusion detection systems (IDS) are used to mitigate these attacks, however, there is a compromise in security and privacy of data ownership between IoT devices. This paper proposes a Federated Ensemble IDS (CNN-GRU and LSTM-GRU) for monitoring IoT network activities using Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Long-Short Term Memory (LSTM) networks that classifies the network as either normal or malicious. Two aggregation functions, including wFedAvg and wFedProx, are developed to create a global model from different clients’ contribution. We perform an evaluation of the proposed IDS on CICIoT2023 and FLNET2023 datasets. The results show that with wFedAvg, the CNN-GRU achieved an accuracy of 98.25% and 99.25% on the CICIoT2023 and FLNET2023 datasets respectively. Additionally, the LSTM-GRU model shows a detection accuracy of 93.36% and 95.66%, respectively on CICIoT2023 and FLNET2023 datasets. The performance shows that the proposed method is robust enough to enhancing the privacy of IoT devices.

关键词： Wireless communication Accuracy Intrusion detection Telecommunication traffic Robustness Internet of Things Convolutional neural networks

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Combining Robust Control and Machine Learning for Uncertain Nonlinear systems Subject to Persistent Disturbances

Combining Robust Control and Machine Learning for Uncertain ...

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IEEE Conference on Decision and Control

作者： A. Banderchuk D. Coutinho E. Camponogara Post-graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis SC Brazil Department of Automation and Systems Universidade Federal de Santa Catarina Florianópolis SC Brazil

This paper proposes a control strategy consisting of a robust controller and an Echo State Network (ESN) based control law for stabilizing a class of uncertain nonlinear discrete-time systems subject to persistent disturbances. Firstly, the robust controller is designed to ensure that the closed-loop system is Input-to-State Stable (ISS) with a guaranteed stability region regardless of the ESN control action and exogenous disturbances. Then, the ESN-based controller is trained in order to mitigate the effects of disturbances on the system output. A numerical example demonstrates the potential of the proposed control design method.

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