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6th IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2023

作者： Oliveira, Franklin Costa, Daniel G. Assis, Flavio Silva, Ivanovitch Federal University of Bahia Graduate Program in Mechatronics Salvador Brazil University of Porto INEGI Faculty of Engineering Porto Portugal Federal University of Rio Grande Do Norte Department of Computer Engineering and Automation Natal Brazil

ISBN: (纸本)9798350396577

The adoption of multi-sensor hardware units to detect different types of emergencies in complex scenarios such as Industry 4.0 and Smart Cities is a recent development trend, which have demanded research efforts to optimize the way these units are assembled, configured, and deployed. However, although their expected advantages, usual multi-sensors emergency-oriented approaches may be constrained by the tight association between physical sensor devices and the emergency detection process. Therefore, this paper proposes an innovative approach to concurrently detect multiple emergencies exploiting the concept of soft-sensor modules, which are implemented on Emergency Detection Units (EDUs) as concurrent tasks along with a high-priority emergency alerting task. The soft-sensor concept defines physical sensors as ordinary input data streams, which will be processed according to the defined algorithms by each particular soft-sensor, allowing detection decisions to be performed on the edge. In order to support the practical exploitation of this concept, a formal specification based on Petri Nets is defined, modeling the concurrent operation of the tasks within an EDU. A proof of concept is also designed based on the affordable Raspberry Pi Pico microcontroller, demonstrating how the proposed approach would behave when two soft-sensors are implemented in a typical detection unit. © 2023 IEEE.

关键词： Industry 4.0

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Balance Control for a Class of Underactuated Systems via Compensation Signals

Balance Control for a Class of Underactuated Systems via Com...

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2022 Chinese automation Congress, CAC 2022

作者： Li, Yue Xin, Xin Yan, Yuhang Southeast University School of Automation Nanjing China Okayama Prefectural University Faculty of Computer Science and Systems Engineering Okayama Japan

ISBN: (纸本)9781665465335

As a typical underactuated experimental platform for robotics and control theory, the rotary inverted pendulum (RIP) system is nonlinear, multi-variable, and strongly coupled. We study the swing-up and balance control for the RIP system with system uncertainty. The classical energy-based swing-up control without compensation for the uncertainty and the signal compensation-based balance control are adopted. In the balance control, from the linearized state-space model near the upright equilibrium point (UEP) and the estimated discrete-time model, a signal compensation-based balance control is constructed to eliminate and suppress the system uncertainty. Simulation results verify the effectiveness of the controllers. © 2022 IEEE.

关键词： State space methods

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Strong stabilization of two-link underactuated planar robots

Strong stabilization of two-link underactuated planar robots

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2022 Chinese automation Congress, CAC 2022

作者： Wang, Ziyu Xin, Xin Liu, Yannian Southeast University School of Automation Nanjing China Okayama Prefectural University Faculty of Computer Science and Systems Engineering Okayama Japan

ISBN: (纸本)9781665465335

Strong stabilization refers to designing stable feedback controllers that stabilize a given plant. The second-order stable stabilizing controller design of two-link underactuated planar robots around their UEP (Upright Equilibrium Point) is concerned in this paper. The proposed method can obtain explicit transfer function of the controller by solving a set of inequalities, which is relatively more concise and the final set of stable controllers is larger than the existing results. Simulation results of both the Acrobot and the Pendubot are presented to verify the effectiveness and robustness of proposed stabilizing controllers. © 2022 IEEE.

关键词： Controllers

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A Novel Determination of Soluble NPK Nutrient Measurement System Using K-means and SOM Methods Compared with UV Visible Spectrophotometer

A Novel Determination of Soluble NPK Nutrient Measurement Sy...

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2023 International Electrical engineering Congress, iEECON 2023

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University of Technology Krungthep Department of Electrical and Telecommunication Engineering Bangkok Thailand Thammasat School of Engineering Thammasat University Faculty of Engineering Department of Electrical and Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department of Robotic Engineering and Automation System Bangkok Thailand

ISBN: (纸本)9798350332360

Technologies are currently being used in smart farms to improve productivity. Agricultural innovation is also widespread. Therefore, the development of Internet of Things (IoTs) technologies and devices to collect data is important. Finding essential nutrients for growth such as Nitrogen (N), Phosphorus (P) and Potassium (K) are important factors. Competitiveness is the important key for growing vertically or indoors. However, soil testing can be expensive, complicated and time consuming. The development of devices that can effectively measure nutrient NPK levels could be used over time. This paper presents a suitable clustering using the K-means method and a forecasting method using the Self-Organizing Map (SOM) method to enhance the device's ability to analyze nutrients in real time. A total of 50,688 samples were tested using the K-Means clustering algorithm, and the sample data were also analyzed. A SOM was prepared to predict the accuracy of the analysis. A total of 11,486 samples were tested and analyzed, then the results of the soluble NPK nutrient monitoring system were taken. It has an efficiency of 84.15% compared to using a UV Visible spectrophotometer, allowing data to be predicted during nutrient solubility changes and to operate according to the proposed system. Therefore, the unsupervised machine learning will improve the measurement system of future cultivation systems. © 2023 IEEE.

关键词： Nutrients

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Swing-Down Control of a Rings Gymnastic Robot

Swing-Down Control of a Rings Gymnastic Robot

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2022 Chinese automation Congress, CAC 2022

作者： Jin, Zhijie Xin, Xin Peng, Zhiyu Liu, Yannian Southeast University School of Automation Nanjing China Okayama Prefectural University Faculty of Computer Science and Systems Engineering Okayama Japan

ISBN: (纸本)9781665465335

In this paper, we study the swing-down control of a rings gymnastic robot, which is a 3-link planar robot moving in a vertical plane with only the last joint being actuated. The control objective is to swing the rings gymnastic robot from the DUU (Down-Up-Up) equilibrium point to the DDD (Down-Down- Down) equilibrium point and stabilize it around the latter. We present an SD (sinusoidal-derivative) controller, which is linear feedback of sinusoidal function of the angle of the actuated joint and linear feedback of its angular velocity. We analyze globally the motion of the rings gymnastic robot under the proposed controller, and provide a sufficient condition for achieving the control goal. We study how to find control gains to achieve an exerllent control performance, and verify the effectiveness of the proposed control via simulation. © 2022 IEEE.

关键词： Motion analysis

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Trajectory Planning and Tracking Control for the Pendubot

Trajectory Planning and Tracking Control for the Pendubot

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2022 Chinese automation Congress, CAC 2022

作者： Xu, Bin Xin, Xin Yan, Yuhang Liu, Yannian School of Automation Southeast University Nanjing China Okayama Prefectural University Faculty of Computer Science and Systems Engineering Okayama Japan

ISBN: (纸本)9781665465335

In this paper, we study the trajectory planning and tracking control for the Pendubot, which is a two-link robot has a single actuator at the base joint of the first link. We realize a fast swing-down control under the sinusoidal-derivative (SD) controller which introduces a damper and spring, and obtain a desired trajectory of the state and the control input by using the swing-down controller and the time-reversal method. To track such a trajectory, we derive the linearized time-varying model of the Pendubot around the trajectory, and design a linear state feedback control along with a feedforward term determined by the trajectory of the control input. We study several obtained trajectories and focus on two issues: 1) the linear controllability of the corresponding linearized time-varying model for each trajectory;2) the sufficient condition in the literature for checking the stability of the tracking control of the linearized time-varying model. Through our numerical investigation, we find that we have to choose appropriate control gains of the SD controller to guarantee the linear controllability, and that the sufficient condition is difficult to be satisfied. © 2022 IEEE.

关键词： Controllability

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Energy-based Swing-up Control with Parameter Optimization for a Rings Gymnastic Robot

Energy-based Swing-up Control with Parameter Optimization fo...

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2022 Chinese automation Congress, CAC 2022

作者： Hu, Jiangyong Xin, Xin Yan, Yuhang Peng, Zhiyu Liu, Yannian Southeast University School of Automation Nanjing China Okayama Prefectural University Faculty of Computer Science and Systems Engineering Okayama Japan

ISBN: (纸本)9781665465335

In this paper, we study a ring gymnastic robot, which is a planar robot with three links moving in the vertical plane with only the last joint activated. First, we use the energy-based strategy to study the swing-up control task of the rings gymnastic robot, and obtain the sufficient and necessary condition for non-existence of singularities in the energy-based controller. Second, we derive the invariant set approached by the closed-loop system. Third, we propose an optimization algorithm to obtain the parameters of the energy-based controller to swing up the rings gymnastic robot into a close neighbourhood of a desired equilibrium point. Fourth, we check on the feasibility of the devised controller and parameter optimization algorithm through simulation. © 2022 IEEE.

关键词： Controllers

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Energy-based Control of Three-Link Planar Robot with Last Active Link

Energy-based Control of Three-Link Planar Robot with Last Ac...

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2022 Chinese automation Congress, CAC 2022

作者： Wang, Yongjia Xin, Xin Liu, Yannian Southeast University School of Automation Nanjing China Okayama Prefectural University Faculty of Computer Science and Systems Engineering Okayama Japan

ISBN: (纸本)9781665465335

This paper studies the energy-based control for a 3-link planar robot with last active link, for which the angle between the last link and the vertical is actuated. The swing-up and stabilizing task around the robot's upright equilibrium point (UEP) is investigated. An energy-based controller is derived to control both its overall energy and actuated variable. By presenting a property of the robot that holds under arbitrary physical parameters, this paper proves that almost all initial states converge to an invariant set where the last link is upright and the robot's overall energy equals its value at the UEP, providing certain requirements on control gains are satisfied. This paper provides simulation verification for the obtained theoretical results, in which a local stabilizing controller is utilized to accomplish stabilization at the UEP. © 2022 IEEE.

关键词： Motion analysis

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The Prediction of COVID-19 Pandemic Situation in Indonesia Using SVR and SIR Algorithm 6

The Prediction of COVID-19 Pandemic Situation in Indonesia U...

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6th International Conference on Information Technology, Information Systems and Electrical engineering, ICITISEE 2022

作者： Yaqin, Ainul Rahardi, Majid Abdulloh, Ferian Fauzi Kusnawi Budiprayitno, Slamet Fatonah, Siti Universitas Amikom Yogyakarta Faculty of Computer Science Yogyakarta Indonesia Institut Teknologi Sepuluh Nopember Vocational Faculty Department of Electrical and Automation Engineering Surabaya Indonesia

ISBN: (纸本)9798350399615

The COVID-19 epidemic, which initially surfaced at the end of 2019, has since expanded to every corner of the globe and has profoundly impacted all facets of human existence. This case started to emerge in Indonesia at the end of February 2020, and until this point, there has been a spike in new patients. Researchers have run several models and projections for COVID-19 cases in Indonesia, but the results are not yet entirely reliable. Predictions produced at the national level must take into account these variations in patterns because this is likely related to the distinct patterns in each region. In this study, the prediction process will be conducted for cases of COVID-19 by using the SVR algorithm and mathematical models to predict reproduction numbers. SVR analysis to overcome the problem of nonlinearity of data in model formation. The modeling is done based on the SIR model, whose parameters are estimated based on the data. Testing result by using 3 kernels is different on each test, prediction of data cases and the level of mistake room are by using Kernel ' RBF ' with a value of C = 1E3, and gamma = 0.1 with the value of MAPE and MSE respectively are 4.5% and 4.2. © 2022 IEEE.

关键词： covid-19 Pandemic Prediction reproduction number SIR Model SVR

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GACL-Net:Hybrid Deep Learning Framework for Accurate Motor Imagery Classification in Stroke Rehabilitation

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computers, Materials & Continua 2025年第4期83卷 517-536页

作者： Chayut Bunterngchit Laith H.Baniata Mohammad H.Baniata Ashraf ALDabbas Mohannad A.Khair Thanaphon Chearanai Sangwoo Kang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Computing Gachon UniversitySeongnam13120Republic of Korea Computer Science Department Faculty of Information TechnologyThe World Islamic Sciences and Education UniversityAmman11947Jordan Intelligent Systems Department Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan IT Infrastructure Department Qatrana Cement CompanyAmman11821Jordan Division of Industrial and Logistics Engineering Technology Faculty of Engineering and TechnologyKing Mongkut’s University of Technology North BangkokRayong CampusRayong21120Thailand

Stroke is a leading cause of death and disability worldwide,significantly impairing motor and cognitive *** rehabilitation is often hindered by the heterogeneity of stroke lesions,variability in recovery patterns,and the complexity of electroencephalography(EEG)signals,which are often contaminated by *** classification of motor imagery(MI)tasks,involving the mental simulation of movements,is crucial for assessing rehabilitation strategies but is challenged by overlapping neural signatures and patient-specific *** address these challenges,this study introduces a graph-attentive convolutional long short-term memory(LSTM)network(GACL-Net),a novel hybrid deep learning model designed to improve MI classification accuracy and ***-Net incorporates multi-scale convolutional blocks for spatial feature extraction,attention fusion layers for adaptive feature prioritization,graph convolutional layers to model inter-channel dependencies,and bidi-rectional LSTM layers with attention to capture temporal *** on an open-source EEG dataset of 50 acute stroke patients performing left and right MI tasks,GACL-Net achieved 99.52%classification accuracy and 97.43%generalization accuracy under leave-one-subject-out cross-validation,outperforming existing state-of-the-art ***,its real-time processing capability,with prediction times of 33–56 ms on a T4 GPU,underscores its clinical potential for real-time neurofeedback and adaptive *** findings highlight the model’s potential for clinical applications in assessing rehabilitation effectiveness and optimizing therapy plans through precise MI classification.

关键词： Motor imagery EEG stroke rehabilitation deep learning brain-computer interface

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