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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Xu Liang Yuchen Yan Tingting Su Zhao Guo Shengda Liu Haojian Zhang Guangping He Department of Mechanical and Electrical Engineering North China University of Technology Beijing China Faculty of Information Technology Beijing University of Technology Beijing China School of Power and Mechanical Engineering Wuhan University Wuhan China Institute of Automation Chinese Academy of Sciences Beijing China

Human-robot interaction torque (HT) plays an important role in the application of lower limb rehabilitation robots. To accurately and quickly obtain the HT applied by the subject during the rehabilitation training, an estimation approach of HT is proposed on the basis of the strong tracking Kalman filter (STKF) and modified moving average method in this paper. First, the dynamics and its corresponding state space model of the human-robot hybrid system are established. Second, the STKF is designed to track the sudden change of the HT rapidly. Based on the hull moving average (HMA) and the weighted moving average (WMA), the hull-weighted moving average with a variable time window (H-WMA) is introduced to improve the estimation accuracy of the HT. Finally, experiments were conducted using a lower limb rehabilitation robot. The experimental results demonstrate its accurate estimation capabilities for assessing the HT. In addition, the proposed method has an effective tracking ability even when the HT changes suddenly.

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Adjusted and controllability Properties of Memristor Rucklidge System

Adjusted and Controllability Properties of Memristor Rucklid...

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2023 IEEE International Conference on Memristive Computing and Applications, ICMCA 2023

作者： Zang, Hongyan Huang, Lili Zhang, Shourong Joseph, Annie Anak Fu, Haiyan Lei, Tengfei Qilu Institute of Technology Collaborative Innovation Center of Memristive Computing Application Jinan250200 China Universiti Malaysia Sarawak Faculty of Engineering Kota Samarahan Sarawak Malaysia College of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan250200 China Shandong Vanform High Energy Physics Technology Co. Ltd. Jinan250100 China Universiti Malaysia Sarawak Department of Electrical and Electronics Kota Samarahan Sarawak Malaysia College of Computer and Information Engineering Qilu Institute of Technology Jinan250200 China Jinan250200 China

ISBN: (纸本)9798350316230

There are many models of memristors, but there are no reports on exponential memristors. In this paper, a three- dimension memristor Rucklidge system with exponential memristor is proposed by introducing exponential function and constructing exponential memristor. The dynamic behavior of the system is analyzed by means of Lyapunov exponent and bifurcation diagram. The complex attractor coexistence and amplitude modulation characteristics of the system are found. The internal variable of memristor is introduced into the second two-dimensional equation as a feedback term, and a conditional symmetric system is constructed for the three-dimensional memristor system, which can realize the polarity control of output signal. By discussing the dynamic characteristics of exponential memristor chaotic system and the control mechanism of amplitude modulation, bias and conditional symmetry, the complex dynamic characteristics of exponential function memristor are revealed, which lays a foundation for its application in the field of secure communication. © 2023 IEEE.

关键词： Memristors

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IEEE Transactions on Instrumentation and Measurement 2024年 1-1页

作者： Wu, Jin Wang, Chaoqun Li, Chong Jiang, Yi Zhang, Chengxi Huang, Yulong Qi, Yuhua Xue, Bohuan Jiao, Jianhao Fan, Rui Zhang, Wei Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China School of Control Science and Engineering Shandong University Jinan China Department of Automation and Measurement Ocean University of China Qingdao China Department of Electrical Engineering City University of Hong Kong Hong Kong China School of Internet of Things Jiangnan University Wuxi China Department of Automation Harbin Engineering University Harbin China School of Systems Science and Engineering Sun Yat-Sen University China College of Electronics and Information Engineering Tongji University Shanghai China

Similarity transformation problems are important in robotic instrumentation and computer vision based measurements since in many cases the information of visually observed scene scale is unknown and must be restored for accurate 3-dimensional reconstruction. In existing solvers, the scale is often considered as a scalar, i.e., isotropic, which may be invalid for anisotropic-scale setups. This paper exploits some mathematical coincidences that will lead to efficient solution to these problems. Possible further applications also include hand-eye calibration and structure-from-motion. We revisit pose estimation problems within the framework of similarity transformation, the one that considers scale-stretching, rotation and translation simultaneously. Two major problems are taken into account, i.e., the scale-stretching point-cloud registration and perspective-n-points (PnP). It has been found out that these two problems are quite similar. Moreover, we solve the anisotropic-scale registration problem that is important and is a remaining unsolved one in previous literatures. To compute the globally optimal solution of these non-convex problems, algebraic solution is obtained to compute all local minima using computationally efficient methods. The designed algorithm is deployed for robotic-arm pose estimation. We also extend the algorithm for solving the problem of robust magnetometer calibration. Visual pose experiments verify the superiority of the proposed method compared with representatives, including P3P, Lambda-Twist P3P and EPnP, which can be reproduced by repository in https://***/zarathustr/APnP. IEEE

关键词： Calibration

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In-situ controller Autotuning by Bayesian Optimization for Closed-loop Feedback control of Laser Powder Bed Fusion Process

arXiv

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arXiv 2024年

作者： Kavas, Barış Balta, Efe C. Tucker, Michael R. Krishnadas, Raamadaas Rupenyan, Alisa Lygeros, John Bambach, Markus Department of Mechanical and Process Engineering ETH Zürich Zürich8092 Switzerland Control and Automation Group Inspire AG Zürich8005 Switzerland Department of Information Technology and Electrical Engineering Automatic Control Laboratory ETH Zürich Zürich8092 Switzerland ZHAW Centre for Artificial Intelligence Zürich University of Applied Sciences Switzerland

Open-loop control of laser powder bed fusion (LPBF) additive manufacturing (AM) has enabled the industrial production of complex and high-criticality parts for aerospace, power generation, medical, transportation, and other industries. This approach relies on static parameter sets obtained through extensive experimentation and a priori simulation on analog parts, with the hope that they remain stable and defect-free once transferred to the production parts. Closed-loop control of LPBF has the potential to enhance process stability further and reduce defect formation in the face of complex thermal histories, stochastic process noise, hardware drift, and unexpected perturbations. The controllers can be classified based on the spatial and temporal scales in which they operate, designated as layer-to-layer and in-layer controllers. However, the performance and effectiveness of controllers largely depend on the tuning of their parameters. Traditionally, controller tuning has been a manual, expertise-driven process that does not guarantee optimal controller performance and is often constrained by the non-transferability of settings between different systems. This study proposes the use of Bayesian Optimization (BO), a sample-efficient algorithm, to automate the tuning of an in-layer controller by leveraging the layer-to-layer repetitive nature of the LPBF process. Two alternative approaches are introduced: online tuning, which adjusts parameters iteratively during the process, and offline tuning, conducted in a representative setup such as laser exposures on a bare metal plate. The proposed methods are experimentally implemented on an in-layer PI controller and the performance of the resulting tuned controllers is investigated on two different wedge geometries that are prone to overheating. The results demonstrate that BO effectively tunes controllers using either method, where both significantly reduced overheating in controlled wedge specimens compared to those uncontro

关键词： controllers

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Thermal Images Based Mobile Application for Identifying Faults in Photovoltaics Modules

Thermal Images Based Mobile Application for Identifying Faul...

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International Symposium on Fundamentals of electrical engineering (ISFEE)

作者： Alexandru-Ionel Constantin Ramona-Nicoleta Banaseanu Paula Anghelita Gabriela Iosif Dorian Marin Department of Renewable Resources and Energy Efficiency National Institute for Research & Development in Electrical Engineering ICPE-CA Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Faculty of Electronics Telecommunications and Information Technology National University of Science and Technology POLITEHNICA Bucharest Office of Management for Knowledge and Information National Institute for Research & Development in Electrical Engineering ICPE-CA

ISBN: (数字)9798350308563

ISBN: (纸本)9798350308570

The paper describes few faults that can be present in Photovoltaic modules and presents results related to training and the testing of a mobile application designed for identifying faults in photovoltaic modules based on thermal images. The mobile application was trained and then tested with different individual and multiple faults. The mobile application can identify with high accuracy both the individual and multiple faults if the thermal images are preprocessed before to be uploaded for analysis.

关键词： Fault diagnosis Training Temperature distribution Temperature dependence Accuracy Thermal engineering Mobile applications

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WaterTS: Integrating Enhanced Transformer, Sliding Block, and Channel Independence for Long-term Water Quality Prediction

WaterTS: Integrating Enhanced Transformer, Sliding Block, an...

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IEEE International Conference on automation Science and engineering (CASE)

作者： Jing Bi Lifeng Xu Ziqi Wang Haitao Yuan Shichao Chen Mu Gu MengChu Zhou Faculty of Information Technology Beijing University of Technology Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences and Beijing Huairou Academy of Parallel Sensing Beijing China Beijing Aerospace Smart Manufacturing Technology Development Co. Ltd Beijing China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Nowadays, the deterioration of water resources leads to negative ecological impacts. To effectively inhibit the deterioration of water resources, a water quality prediction model based on enhanced transformer, sliding block, and channel independence (WaterTS) is proposed by comprehensively analyzing the indicators of water resources and making long-term predictions of the dissolved oxygen index. WaterTS adopts a sliding block method to extract the short-term temporal features of the water quality series and combine them with channel independence to make independent predictions of multi-featured data. Moreover, it upgrades the internal encoder structure of the transformer and improves the attention mechanism to Probsparse-attention and Auto-Correlation to speed up the prediction speed. Furthermore, Post LayerNormal is adjusted to Pre LayerNormal, which makes the training gradient more stable and enhances the accuracy of predictions. Experiments are conducted using real-world water environment data, and comparison results with state-of-the-art prediction models show that the WaterTS achieves accurate predictions on both short-term and long-term water quality data.

关键词： Training Accuracy Biological system modeling Time series analysis Water quality Predictive models Transformers Feature extraction Real-time systems Water resources

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Distance-based Multiple Non-cooperative Ground Target Encirclement for Complex Environments

arXiv

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arXiv 2024年

作者： Liu, Fen Yuan, Shenghai Cao, Kun Meng, Wei Xie, Lihua School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200000 China Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control School of Automation Guangdong University of Technology Guangzhou510006 China

This paper proposes a comprehensive strategy for complex multi-target-multi-drone encirclement in an obstacle-rich and GPS-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithm’s effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach. © 2024, CC BY.

关键词： Drones

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A Convolutional Neural Network for skin lesion classification in Dermoscopic Images using discrete wavelet transform

A Convolutional Neural Network for skin lesion classificatio...

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European control Conference (ECC)

作者： Miron Mihaela Anisia Luiza Culea-Florescu Simona Moldovanu Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Galați Dunarea de Jos University of Galati 47 Domneasca Str. Galati Romania Department of Electronics and Telecommunications Faculty of Automation Computers Electrical Engineering and Electronics Galați Dunarea de Jos University of Galati 47 Domneasca Str. Galati Romania

The objective of this paper is to investigate a new technique for skin lesion classification based on discrete wavelet transforms and convolutional networks. More precisely, for preprocessing the images, two 2D family wavelets and Low-Low (LL), High-High (HH) bands were used to generate subimages for each skin lesion image as melanoma and normal nevi. On each subimage datasets of nevi and melanoma, five convolutional neural networks (CNNs) were tested. The experiments were conducted on the public Mednode dataset which contains 170 images (70 melanoma and 100 nevi cases). The accuracy, precision, recall, and F1-score metrics were extracted from confusion matrix for each test performed on the proposed CNN architecture. All metrics show that LL subimages are recommended to be used in classifying melanoma vs. nevi.

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Iris-Based Biometric Identification Using a Combination of the Right - Left Iris Statistical Features 12

Iris-Based Biometric Identification Using a Combination of t...

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12th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2023

作者： Dincǎ Lǎzǎrescu, A.M. Moldovanu, S. Moraru, L. The Modelling & Simulation Laboratory Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Mihail Kogǎlniceanu High School 161B Brǎilei St. Galati800320 Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Department of Chemistry Physics & Environment Faculty of Sciences and Environment Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania

A combination between the information extracted for both right iris and left iris could increase the efficacy of the biometric recognition systems. In this paper, we propose a biometric identification method based on density of image patterns extracted from human iris images and the combination and comparison of the right iris and the left iris characteristics. The density of the patters approach for processed images can be a new biometric feature used to implement a biometric recognition system with high performance when a small feature dimension is used. In this way, we can maximize the retention of the effective biometric information. The experiments were conducted on the MMU Iris Database containing 225 images of the left eye and 225 images of the right eye. Two morphological Top-hat and Hit or Miss transforms were implemented to find out the particular pattern of pixels. They allow for the enhancement of detail in images. Then, a statistical feature extraction technique is employed to derive the density of the patterns in morphological transformed images. To assess the density of the patterns differences between the right and left iris data groups, the Pearson's correlation coefficient (PCC) is computed. We reported very good results with a PCC of 0.6164 (strong and positive correlation) for Top-hat morphological operation whilst the Hit or Miss transform returns a PCC of 0.0127 so there is no relationship between the density of the patterns in the right and left irises. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Biometrics

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Multi-population Cooperative Particle Swarm Optimization Algorithm and Its Application to Hyperparameter Optimization of Neural Network Model

Multi-population Cooperative Particle Swarm Optimization Alg...

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第34届中国过程控制会议

作者： Jiulin Sun Yanbo Chen Haiyan Li Mi Li Department of Automation Faculty of Information TechnologyBeijing University of Technology Beijing International Collaboration Base on Brain Informatics and Wisdom Services Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Engineering Research Center of Digital Community Ministry of Education

The lack of effective communication and cooperation among subpopulations leads to subpopulation aggregation,which affects the movement direction and search accuracy of the *** this study,we propose a multi-population cooperative particle swarm optimization(MCPSO) to improve communication and cooperation among *** MCPSO,we reconstruct the population optimal position(gbest) and subpopulation optimal position(lbest).Additionally,we establish exploration,exploitation,and auxiliary subpopulations and assign them different *** results using the CEC2017test function in three dimensions(30,50,and 100) demonstrate the superior performance of *** applied to hyperparameter optimization of neural network model,the results show that MCPSO outperforms other PSO algorithms,thereby validating its effectiveness and practicality.

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