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Design of an adaptive fuzzy-neural inference system-based control approach for robotic manipulators

Applied Soft Computing 2023年第PartA期149卷

作者： Barhaghtalab, Mojtaba Hadi Sepestanaki, Mohammadreza Askari Mobayen, Saleh Jalilvand, Abolfazl Fekih, Afef Meigoli, Vahid Department of Electrical Engineering Faculty of Engineering University of Zanjan Zanjan Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin640301 Taiwan Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA70504 United States Department of Electrical Engineering Faculty of Engineering Persian Gulf University Bushehr Iran

This paper proposes an adaptive fuzzy-neural inference system (ANFIS)-based control approach for a six degrees of freedom (6-DoF) robotic manipulator. Its main objective is to guarantee the error convergence of the controlled system in the presence of uncertainties and unknown disturbances. The suggested controller is a parallel combination of an ANFIS network with a proportional-integral-derivative (PID) controller. The ANFIS system is used as an estimator to approximate a part of the system and then applied as the feedback linearization in the suggested control structure. The convergence of system errors to zero was proven using Barbalat's lemma. The suggested control law combines the simplicity and ease of implementation of PID control with the estimation properties of ANFIS networks. The suggested approach was evaluated using a simulation study and further validated experimentally using the 6-DoF IRB-120 robotic manipulator (IRB-120-RM). The obtained results confirmed its superior performance and suitability for practical implementation to industrial actuators. © 2023 Elsevier B.V.

关键词： Feedback linearization

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A Large Reservoir Computing Forecasting Method Based on Randomized Fuzzy Cognitive Maps

A Large Reservoir Computing Forecasting Method Based on Rand...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Omid Orang Fabricio J. Erazo-Costa Petrônio C. L. Silva Guilherme de Alencar Barreto Frederico Gadelha Guimarães Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte Brazil Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Federal Institute of Northern Minas Gerais Januária Campus Brazil Department of Teleinformatics Engineering Universidade Federal do Ceará Fortaleza Brazil

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

This paper introduces a novel forecastings technique based on randomized fuzzy cognitive maps (FCM), called LRHFCM (or large reservoir of randomized high-order FCM) for predicting univariate time series. LR-HFCM is a hybrid method combining fuzzy time series (FTS), FCMs, and reservoir computing. It is a type of echo state network (ESN) consisting of the input layer, intermediate (or large reservoir) layer, and output layer, where LASSO regression is applied to train the output layer. The novelty of this approach is that the internal layer includes a very large reservoir, considering different combinations from the sets of concepts and order using a certain number of sub-reservoirs to capture different dynamics of input time series. It is important to highlight that the weights within each sub-reservoir are chosen randomly and remain constant throughout the training process. The validity of the LR-HFCM approach is evaluated across 15 different time series datasets. The results highlight the outperformance of the LR-HFCM technique in comparison to various baseline models.

关键词： Training Adaptation models Adaptive systems Computational modeling Time series analysis Fuzzy cognitive maps Reservoirs

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Load Profile Effect on Shunt Capacitor Placement in Radial Distribution Feeders

Load Profile Effect on Shunt Capacitor Placement in Radial D...

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IEEE Kansas Power and Energy Conference

作者： Meisam Mahdavi Augustine Awaafo Konrad Schmitt Manohar Chamana Department of Electrical Engineering University of Jaén Linares Jaén Spain Electrical and Computer Engineering Department Texas Tech University Lubbock TX USA Renewable Energy Program Texas Tech University Lubbock USA

Capacitor placement in electric power systems is an effective way to minimize energy losses, especially in distribution systems, where power losses are more than transmission ones. On the other hand, time-varying load levels affect energy losses amount in such networks. Therefore, load profile has an important role in determining the amount of power losses and the optimal place of shunt capacitors in radial feeders. However, embedding load variability in the capacitor placement problem enhances the computational burden and processing time, while its ignorance leads to inaccurate calculation of energy losses and subsequent optimal locations of capacitor banks. Hence, most of specialized studies have ignored load changes in their capacitor placement models because of computational burden and processing time increase. Accordingly, the present paper intent to evaluate the effect of consumption patterns on capacitor placement proposals in order to understand the importance of load variability consideration in reducing power losses through reactive power compensation. The analysis has been carried out using a mathematical programming language in several distribution systems.

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A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models

arXiv

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arXiv 2025年

作者： Xu, Ziqing Min, Hancheng Tarmoun, Salma Mallada, Enrique Vidal, René Department of Statistics and Data Science the Wharton School University of Pennsylvania United States University of Pennsylvania United States Graduate Group in Applied Mathematics and Computational Science University of Pennsylvania United States Department of Electrical and Computer Engineering Johns Hopkins University United States Department of Electrical and Systems Engineering Department of Radiology University of Pennsylvania United States

Most prior work on the convergence of gradient descent (GD) for overparameterized neural networks relies on strong assumptions on the step size (infinitesimal), the hidden-layer width (infinite), or the initialization (large, spectral, balanced). Recent efforts to relax these assumptions focus on two-layer linear networks trained with the squared loss. In this work, we derive a linear convergence rate for training two-layer linear neural networks with GD for general losses and under relaxed assumptions on the step size, width, and initialization. A key challenge in deriving this result is that classical ingredients for deriving convergence rates for nonconvex problems, such as the Polyak-Lojasiewicz (PL) condition and Descent Lemma, do not hold globally for overparameterized neural networks. Here, we prove that these two conditions hold locally with local constants that depend on the weights. Then, we provide bounds on these local constants, which depend on the initialization of the weights, the current loss, and the global PL and smoothness constants of the non-overparameterized model. Based on these bounds, we derive a linear convergence rate for GD. Our convergence analysis not only improves upon prior results but also suggests a better choice for the step size, as verified through our numerical experiments. © 2025, CC BY.

关键词： Dynamic models

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Algorithm-Hardware Co-Design for Wearable BCIs: An Evolution from Linear Algebra to Transformers

Algorithm-Hardware Co-Design for Wearable BCIs: An Evolution...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Sunyoung Park Wooseok Byun Minkyu Je Ji-Hoon Kim Department of Electronic and Electrical Engineering Ewha Womans University Seoul Republic of Korea Graduate Program in Smart Factory Ewha Womans University Seoul Republic of Korea SAPEON Korea Inc Seongnam Republic of Korea School of Electrical Engineering KAIST Daejeon Republic of Korea

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Recent advancements in brain-computer interface (BCI) technology for steady-state visual evoked potential (SSVEP)-based target identification have shifted from traditional linear algebra (LA) techniques to more sophisticated neural network (NN) approaches, driven by their increased accuracy and consistent performance across different subjects. However, adopting NN-based algorithms has introduced complexities in wearable BCI systems, mainly due to their extensive parameter sets that demand significant memory capacity. Moreover, the computational intensity of these models requires reevaluating hardware architectures. Additionally, the advent of Transformer-based models has further advanced the state of the art, providing even higher accuracy and reduced variability in cross-subject performance, placing greater demands on hardware resources. This paper provides an overview of recent algorithmic progress in SSVEP-based target identification. Also, it proposes considerations for the hardware architecture needed to efficiently support the computation of cutting-edge Transformer-based models in wearable BCIs from the perspective of algorithm-hardware co-design.

关键词： Visualization Accuracy Computational modeling computer architecture Artificial neural networks Linear algebra Transformers

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Metasurfaces for Molecular Emitter

Metasurfaces for Molecular Emitter

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Yoshiaki Nishijima Department of Electrical and Computer Engineering Graduate School of Engineering Yokohama National University Hodogaya-ku Yokohama Japan

We demonstrate extraordinarily spectrally selective narrowband mid-infrared radiation absorbance and thermal emittance with the strong surface enhancement of molecular infrared absorption (SEIRA) using mid-midinfrared metasurfaces. This was achieved by harnessing mode coupling between a plasmonic metal-insulator-metal (MIM) metasurface and molecular vibrational mode resonances. We found that the weak/strong coupling has a high potential for the future application of thermal emitters for midinfrared light sources. We will present recent advances in the coupling of molecular vibration and metasurfaces.

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Inverse Design of Plexcitonic Metasurfaces for Broadband Nonlinear Frequency Conversion

Inverse Design of Plexcitonic Metasurfaces for Broadband Non...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Almeida, Euclides Feinstein, Matthew Andronikides, Alexander Blechman, Yael Bartal, Guy Queens College City University of New York FlushingNY11367 United States The Graduate Center of the City University of New York New YorkNY10016 United States Andrew and Erna Viterbi Department of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa32000 Israel

ISBN: (纸本)9781957171258

Using inverse design, we demonstrate a plexcitonic metasurface of monolayer WS2 strongly coupled to gold nanoantennas. Broadband third-harmonic generation is attained over the entire plexcitonic frequencies. We discuss optimization strategies and implications for nonlinear photonics. © Optica Publishing Group 2023 © 2023 The Author(s)

关键词： Tungsten compounds

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Ambient Cardiovascular Monitoring with Metamaterial Textile Sensors

Ambient Cardiovascular Monitoring with Metamaterial Textile ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Dat T. Nguyen Qihang Zeng Xi Tian John S. Ho Integrative Sciences and Engineering Program National University of Singapore Graduate School Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore SIA-NUS Digital Aviation Corporate Laboratory and the Institute for Health Innovation and Technology National University of Singapore Singapore Department of Electrical and Computer Engineering Institute for Health Innovation and Technology N.1 Institute for Health at the National University of Singapore Singapore

Contactless sensors embedded in the ambient environment have broad applications in unobtrusive, long-term health monitoring for preventative and personalized healthcare. Microwave radar sensors are an attractive candidate for ambient sensing due to their high sensitivity to physiological motions, ability to penetrate through obstacles and privacy-preserving properties, but practical applications in complex real-world environments have been limited because of challenges associated with background clutter and interference. In this work, we propose a thin and soft textile sensor based on microwave metamaterials that can be easily integrated into ordinary furniture for contactless ambient monitoring of multiple cardiovascular signals in a localized manner. Evaluations of our sensor’s performance in human subjects show high accuracy of heartbeat and arterial pulse detection, with ≥ 96.5% sensitivity and < 5% mean absolute relative error (MARE) across all subjects. We demonstrate our sensor’s utility for cuffless blood pressure monitoring on a human subject over a continuous 10-minute period. Our results highlight the potential of metamaterial textile sensors in ambient health and wellness monitoring *** relevance—The contactless metamaterial textile sensors demonstrated in this paper provide unobtrusive, convenient and long-term monitoring of multiple cardiovascular health metrics, including heart rate, pulse rate and cuffless blood pressure, which can facilitate preventative and personalized healthcare.

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RoboRover – A Jetson Nano Powered Robot Car for Object Following, Obstacle Avoidance, and Wall Following

RoboRover – A Jetson Nano Powered Robot Car for Object Foll...

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IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Trinh Huynh James Walter Federica Aveta Robotics Department University of Michigan Ann Arbor Michigan USA Electrical and Computer Engineering Program Wentworth Insitute of Technology Boston Massachusetts USA

An intelligent and self-sufficient robot is essential across a wide range of fields, including transportation, industry, space exploration, and defense. Mobile robots possess the capability to undertake diverse tasks such as handling materials, aiding in disaster scenarios, conducting patrols, and executing rescue operations. As a result, the development of an autonomous robot that can navigate through both unchanging and ever-changing surroundings has become important. The primary objective of mobile robot navigation revolves around ensuring the seamless and secure traversal of the robot through complex environments, starting from an initial position, and reaching a designated goal position. This paper presents the design and implementation of a Jetson Nano powered robot car which uses local sensors to interact with an unknown environment. Object following, obstacle avoidance, and wall following features are built for the car to navigate to reach its desired destinations.

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Verification of the Inactivation Effect of Near-UV LEDs using a Pulsed Lighting System on Staphylococcus aureus

Verification of the Inactivation Effect of Near-UV LEDs usin...

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Sustainable Smart Lighting World Conference & Expo (LS18), IEEE

作者： Hiroki Nomura Seiji Kihara Akinori Zukeran Jun Sawai Takayuki Misu Graduate School of Engineering Master's Degree Program in Electrical and Electronic Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan Department of Electrical and Electronic Engineering Faculty of Engineering Kanagawa Institute of Technology Atsugi Kanagawa Japan Department of Nutrition and Life Science Faculty of Health and Medical Sciences Kanagawa Institute of Technology Atsugi Kanagawa Japan

ISBN: (数字)9798331540197

ISBN: (纸本)9798331540203

The purpose of this study is to investigate the disinfection effect of Near-UV LED light, which is pulsed using PWM control, on Staphylococcus aureus. To evaluate the disinfection effect of Near-UV LED light, three types of Near-UV LEDs with wavelengths of 395 nm, 385 nm, and 365 nm were installed within a sealed space inside an incubator and energized with a forward current of 1000 mA and a forward voltage of 3.6 V, and the disinfection rate under each type of light was assessed. Additionally, the disinfection effect was evaluated when the same three types of Near-UV LEDs were pulsed with a 50% duty cycle. As a result, 100% disinfection was achieved with 365 nm Near-UV LED direct-current irradiation for 120 seconds, and a 93% disinfection rate was obtained with pulsed irradiation for 150 seconds.

关键词： Radiation effects Power demand Lighting Pulse width modulation Aerospace electronics Light emitting diodes

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