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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...

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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...

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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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Safe Receding Horizon Motion Planning with Infinitesimal Update Interval

Safe Receding Horizon Motion Planning with Infinitesimal Upd...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Inkyu Jang Sunwoo Hwang Jeonghyun Byun H. Jin Kim Department of Aerospace Engineering and Automation and Systems Research Institute (ASRI) Seoul National University Seoul Korea Department of Aerospace Engineering and Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University Seoul Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Safety verification in motion planning is known to be computationally burdensome, despite its importance in robotics. In this paper, we investigate the behavior of safe receding horizon motion planners when the update interval becomes infinitesimal. By requiring the trajectory parameters to evolve continuously in time, the trajectory optimization problem is reformulated into a time-derivative form, whose decision variables are their rate of change. This results in a quadratic programming problem which directly provides safe input, and can be regarded as a real-time safety filter. The input expressivity is also enhanced by leveraging the differentiable structure of the parameter space. The proposed safety filter is experimentally validated using a wheeled ground robot in obstacle-cluttered environments. The result shows that the safety filter is capable of generating safe inputs in real-time, while addressing hundreds of constraints simultaneously.

关键词： Uncertainty Computational modeling Real-time systems Libraries Safety Planning Numerical models

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Comparative analysis of bioinspired algorithms for tuning a flatness-based controller: A ball and beam case study

Comparative analysis of bioinspired algorithms for tuning a ...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： M. A. Pastrana José Oniram de A. Limaverde Filho Luiz Henrique Oliveira Jaider Bautista Eugênio Fortaleza Daniel M. Muñoz Department of Mechanical Engineering Automation and Control Group (GRACO) University of Brasília Brasília Brazil Department of Electrical Engineering University of Brasília Brasília Brazil Faculty of Engineering Systems Undergraduate Program University of the Amazonia Florencia Colombia

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

This paper provides a comprehensive comparative analysis of the performance of four bioinspired algorithms (Differential Evolution, Grasshopper Optimization Algorithm, Moth-flame Optimization, and Particle Swarm Optimization) in designing a flatness-based controller for a ball and beam system simulated in MATLAB/Simulink environment. The assessment involves the tuning of feedback gains utilizing four distinct fitness functions: Integral Square Error, Integral Absolute Error, Integral Time Absolute Error, and an ad-hoc cost function. Hypothesis tests are employed to choose the optimal controllers from each combination for every bioinspired algorithm and a fitness function. Subsequently, a control performance analysis of these controllers for the ball and beam system is conducted, focusing on critical parameters such as overshoot, settling time, and steady-state error. This analysis demonstrates that all the controllers achieve a zero steady-state error. Noteworthy is the flatness-based controller tuned with the bioinspired Grasshopper Optimization Algorithm and utilizing the Integral Time Absolute Error fitness function, which stands out for achieving the fastest response with the lowest overshoot. This particular controller emerges as the most recommended choice for the specified application.

关键词： Particle beams Focusing Cost function MIMO Steady-state Performance analysis Particle swarm optimization MATLAB Tuning Computational intelligence

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Developing a Floating Robot for Mechanical Control of Water Hyacinth 3

Developing a Floating Robot for Mechanical Control of Water ...

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3rd International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2023

作者： Elsayed, Mostafa E.A. Mohamed, Ahmed K.A. Shaaban, Mahmoud Abdelrahman, Mohamed A. Ahmed, Mohamed E. A. E. Rashed, Mostafa R. Benha University Automation and Energy Technology Lab. Shoubra Faculty of Engineering Mechanical Engineering Department Cairo Egypt Benha University Agricultural Power and Machinery Faculty of Agriculture Department of Agricultural Engineering Kalubia Egypt School of Engineering and Applied Sciences Nile University Smart Engineering Systems Center Mechanical Engineering Program Giza Egypt Benha University Combustion and Energy Technology Lab. Shoubra Faculty of Engineering Mechanical Engineering Department Cairo Egypt Benha University Shoubra Faculty of Engineering Mechanical Engineering Department Cairo Egypt University for Technology and Information Faculty of Engineering Modern Mechanical Engineering Department Cairo Egypt

ISBN: (纸本)9798350306231

Water hyacinth has become widespread in freshwater bodies in several countries, leading to various issues, particularly its substantial water consumption and the resulting need to control its growth. Among the different methods of controlling water hyacinth, mechanical control stands out as the most effective and environmentally friendly approach. A proposed harvester robot has been developed, capable of efficiently cutting and collecting water hyacinth from the water's surface. The robot boasts several advantages, including its ability to operate in narrow water paths and lakes, use clean energy sources to preserve the water ecology, employ a GPS module for safety and error detection, and generate maps for evaluating work and predicting annual growth. When compared to other technologies dealing with water hyacinth, this innovative water hyacinth harvesting robot presents a significantly lower cost of 0.01 /kg, making it an optimal solution for addressing water hyacinth problems. © 2023 IEEE.

关键词： Weed control

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Learn2Evade: Learning-based generative model for evading PDF malware classifiers

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2021年第4期2卷 299-313页

作者： Bae, Ho Lee, Younghan Kim, Yohan Hwang, Uiwon Yoon, Sungroh Paek, Yunheung Department of Cyber Security EwhaWomans University Seoul03760 Korea Republic of Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Interdisciplinary Program in Bioinformatics Interdisciplinary Program in Artificial Intelligence Automation and Systems Research Institute Institute of NewMedia and Communications Institute of Engineering Research Seoul National University Seoul08826 Korea Republic of

Recent research has shown that a small perturbation to an input may forcibly change the prediction of a machine learning (ML) model. Such variants are commonly referred to as adversarial examples. Early studies have focused mostly on ML models for image processing and expanded to other applications, including those for malware classification. In this article, we focus on the problem of finding adversarial examples against ML-based portable document format (PDF) malware *** deem that our problem is more challenging than those againstMLmodels for image processing because of the highly complex data structure of PDF and of an additional constraint that the generated PDF should exhibit malicious behavior. To resolve our problem, we propose a variant of generative adversarial networks that generate evasive variant PDF malware (without any crash), which can be classified as benign by various existing classifiers yetmaintaining the original malicious behavior. Our model exploits the target classifier as the second discriminator to rapidly generate an evasive variant PDF with our new feature selection process that includes unique features extracted from malicious PDF files. We evaluate our technique against three representative PDF malware classifiers (Hidost 13, Hidost 16, and PDFrate-v2) and further examine its effectiveness with AntiVirus engines from VirusTotal. To the best of our knowledge, our work is the first to analyze the performance against the commercial AntiVirus engines. Our model finds, with great speed, evasive variants for all selected seeds against state-of-The-Art PDF malware classifiers and raises a serious security concern in the presence of adversaries. © 2021 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Generative adversarial networks

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A cryptographic system based on automata for Networked automation systems abstracted as Discrete-Event systems

A cryptographic system based on automata for Networked Autom...

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IEEE International Conference on automation Science and engineering (CASE)

作者： Marcos V. Moreira Publio M. M. Lima Lilian K. Carvalho Felipe G. Cabral COPPE - Electrical Engineering Program Universidade Federal do Rio de Janeiro Cidade Universitária Rio de Janeiro RJ Brazil Department of Automation and Systems Federal University of Santa Catarina Florianópolis SC Brazil

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

One of the main concerns about implementing Networked automation systems is ensuring its security against cyber-attacks. In this paper, we consider that the Networked automation System is abstracted as a Discrete-Event System, and we consider cyber-attacks where a malicious agent eavesdrops on a communication channel with the objective of gathering information about the system’s behavior. To protect the information transmitted in the attacked channel, we propose a cryptographic system that uses Mealy automata to represent the encryption and decryption functions. One of the main advantages of representing cryptographic systems using automata is that they can be easily implemented on programmable Logic Controllers, yielding to fast encryption and decryption of the transmitted message.

关键词： automation Computer aided software engineering programmable logic devices Automata Rotors Communication channels Encryption Discrete-event systems Complexity theory Cyberattack

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Homogenization Technique of Magnetostriction Calculation in Laminated Iron Core

Homogenization Technique of Magnetostriction Calculation in ...

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International Conference on Electrical Machines and systems (ICEMS)

作者： Yanhui Gao Hiroki Fujita Weimin Guan Kazuhiro Muramatsu Intelligent Mechanical Systems Program Oita University Oita Japan School of Electrical Engineering and Automation Wuhan University Wuhan P. R. China Department of Electrical and Electronic Engineering Saga University Saga Japan

Accurate displacement calculation in the laminated iron cores of electric machines is important for the accurate prediction of noise generation in the electric machines. The authors proposed a modeling method of displacements due to magnetostriction in the laminated iron core using a homogenization model with equivalent anisotropic magnetic and elastic parameters. The calculated displacements obtained from the homogenization model are compared with those of the real laminated iron core model, and the solid core model neglecting the laminated structure. The homogenization model shows good agreement with the real model.

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