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arXiv 2019年

作者： Liu, Shenglan Yu, Yang Liu, Yang Qiao, Hong Feng, Lin Feng, Jiashi School of Computer Science and Technology Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian Liaoning116024 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore

Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution, data sparsity is always a thorny knot. There are few researches to well handle it in manifold learning. In this paper, we propose Hierarchic Neighbors Embedding (HNE), which enhance local connection by the hierarchic combination of neighbors. After further analyzing topological connection and reconstruction performance, three different versions of HNE are given. The experimental results show that our methods work well on both synthetic data and high-dimensional real-world tasks. HNE develops the outstanding advantages in dealing with general data. Furthermore, comparing with other popular manifold learning methods, the performance on sparse samples and weak-connected manifolds is better for HNE. Copyright © 2019, The Authors. All rights reserved.

关键词： Topology

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Active disturbance rejection control design with suppression of sensor noise effects in application to DC-DC buck power converter

arXiv

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arXiv 2020年

作者： Lakomy, Krzysztof Madonski, Rafal Dai, Bin Yang, Jun Kicki, Piotr Ansari, Maral Li, Shihua The Poznaá Universitńy of Technology Poznan60-965 Poland The Energy Electricity Research Center International Energy College Jinan University Zhuhai519070 China The School of Automation Southeast University Key Laboratory of Measurement and Control of CSE Ministry of Education Nanjing210096 China The Institute of Robotics and Machine Intelligence Poznań University of Technology Poznań60-965 Poland The Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW2007 Australia

The performance of active disturbance rejection control (ADRC) algorithms can be limited in practice by high-frequency measurement noise. In this work, this problem is addressed by transforming the high-gain extended state observer (ESO), which is the inherent element of ADRC, into a new cascade observer structure. Set of experiments, performed on a DC-DC buck power converter system, show that the new cascade ESO design, compared to the conventional approach, effectively suppresses the detrimental effect of sensor noise over-amplification while increasing the estimation/control performance. The proposed design is also analyzed with a low-pass filter at the converter output, which is a common technique for reducing measurement noise in industrial applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Spurious signal noise

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GPPT: Graph pyramid pooling transformer for visual scene

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Neurocomputing 2025年 647卷

作者： Zhi-Peng Li Wen-Jian Liu Xin Sun Yi-Jie Pan Valeriya Gribova Vladimir Fedorovich Filaretov Anthony G. Cohn De-Shuang Huang Ningbo Institute of Digital Twin Eastern Institute of Technology Tongxin Road No. 568 Ningbo Zhejiang 315201 China Faculty of Data Science City University of Macau 999078 Macao MEGAROBO Technologies Linglong Street No. 88 Suzhou Jiangsu 215128 China College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing Jiangsu 211106 China Institute of Automation and Control Processes Far Eastern Branch of Russian Academy of Sciences Russia School of Computing University of Leeds Leeds LS2 9JT UK Institute for Regenerative Medicine Medical Innovation Center and State Key Laboratory of Cardiology Shanghai East Hospital School of Life Sciences and Technology Tongji University Shanghai 200123 China

In the field of computer vision, network architectures are critical to the performance of tasks. Vision Graph Neural Network (ViG) has shown remarkable results in handling various vision tasks with their unique characteristics. However, the lack of multi-scale information in ViG limits its expressive capability. To address this challenge, we propose a Graph Pyramid Pooling Transformer (GPPT), which aims to enhance the performance of the model by introducing multi-scale feature learning. The core advantage of GPPT is its ability to effectively capture and fuse feature information at different scales. Specifically, it first generates multi-level pooled graphs using a graph pyramid pooling structure. Next, it encodes features at each scale using a weight-shared Graph Convolutional Neural Network (GCN). Then, it enhances information exchange across scales through a cross-scale feature fusion mechanism. Finally, it captures long-range node dependencies using a transformer module. The experimental results demonstrate that GPPT achieves exceptional performance across various visual scenes, including image classification, and object detection, highlighting its generality and validity.

关键词： Convolutional neural networks

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Nonlinear Predictive control Applied to Steam/Water Loop in Large Scale Ships

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IFAC-PapersOnLine 2019年第1期52卷 868-873页

作者： Shiquan Zhao Ricardo Cajo Robin De Keyser Sheng Liu Clara M. Ionescu Faculty of Engineering and Architecture Ghent University Research group on Dynamical Systems and Control Technologiepark 914 B9052 Zwijnaarde Belgium College of Automation Harbin Engineering University China Core Lab EEDT- Energy Efficient Drive Trains Flanders Make Grupo de Investigación en Automatización y Control Industrial Campus Gustavo Galindo Km 30.5 Vía Perimetral P.O. Box 09-01-5863 Guayaquil Ecuador Technical University of Cluj Napoca Department of Automatic Control Memorandumului Street no 28 Cluj Romania

In steam/water loop for large scale ships, there are mainly five sub-loops posing different dynamics in the complete process. When optimization is involved, it is necessary to select different prediction horizons for each loop. In this work, the effect of prediction horizon for Multiple-Input Multiple-Output (MIMO) system is studied. Firstly, Nonlinear Extended Prediction Self-Adaptive controller (NEPSAC) is designed for the steam/water loop system. Secondly, different prediction horizons are simulated within the NEPSAC algorithm. Based on simulation results, we conclude that specific tuning of prediction horizons based on loop’s dynamic outperforms the case when a trade-off is made and a single valued prediction horizon is used for all the loops.

关键词： Nonlinear predictive control Prediction horizon Steam power plant Steam/water loop Multi-Input Multi-Output

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A comparative study above two self-tuning controllers with aplication to the control of synchronous generator excitation system

arXiv

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arXiv 2018年

作者： Filip, Ioan Curiac, Daniel Prostean, Octavian Szeidert, Iosif "Politehnica" University of Timisoara Faculty of Control Engineering and Computer Sciences Department of Automation and Industrial Informatics

This paper presents two self-tuning control structures synthesized through the minimization of two criterion functions. It is described the computation methodology of the control laws, both being particularized for the case of the synchronous generator's excitation control. The parameters estimator is considered the recursive least square error (RLSE) algorithm. In order to validate the considered control structures, two comparative study cases by computer simulation are presented. Copyright © 2018, The Authors. All rights reserved.

关键词： Adaptive control systems

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Generation and Capture of Electric Energy Using Piezoelectric Materials: A Review

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IOP Conference Series: Materials Science and engineering 2021年第1期1154卷

作者： A D Rincón-Quintero C L Sandoval-Rodriguez N D Zanabria-Ortigoza C G Cárdenas-Arias J G Ascanio-Villabona M A Durán-Sarmiento Design and materials research group (DIMAT) Automation and Control Energy Systems Research Group (GISEAC) Electromechanical engineering Faculty of Natural Sciences and Engineering Unidades Tecnológicas de Santander (UTS) Calle de los estudiantes No 9-82 680005 Bucaramanga Colombia Doctoral Program in Energy Efficiency and Sustainability in Engineering and Architecture Department of Machines and Thermal Engines University of the Basque Country UPV/EHU 48013 Bilbao Spain Doctoral Program in Electronic and Communications Department of Communications Engineering University of the Basque Country UPV/EHU 48013 Bilbao Spain Doctoral Program in Engineering of Materials and Sustainable Processes University of the Basque Country UPV/EHU 48013 Bilbao Spain

Piezoelectricity comes as a principle of transformation of mechanical energy into electrical energy, it is limited in terms of investment, time and research, due to this fact, the need arises to be able to innovate with data collection on the most used models to collect and generate electrical energy. In this research, the literature regarding the generation and collection of electrical energy using piezoelectric materials was analyzed, from this analysis, fifty innovative articles were determined in the last three years, which were reflected in a data matrix, in which It presents the generation and collection element, the applications, and shows the performance in terms of power or voltage that the prototypes supply. With the results of the table, a condensed panorama of current data is obtained, about the most used and outstanding of this form of little-used energy, but which is a competent and efficient alternative for the generation of electricity.

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Electromechanical Hand Prototype for the Simulation of the Opening and Closing Movement

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IOP Conference Series: Materials Science and engineering 2021年第1期1154卷

作者： C L Sandoval-Rodriguez E Y Veslin-Díaz B E Tarazona-Romero J G Ascanio-Villabona C G Cárdenas-Arias C A Angulo-Julio Energy Systems Automation and Control Research Group (GISEAC) Design and materials research group (DIMAT) Electromechanical Engineering Faculty of Natural Sciences and Engineering Unidades Tecnologicas de Santander (UTS) Road No 9-82 students 680005 Bucaramanga Colombia Doctoral Program in Electronic and Communications Department of Communications Engineering University of the Basque Country UPV/EHU 48013 Bilbao Spain Doctoral Program in Energy Efficiency and Sustainability in Engineering and Architecture Department of Machines and Thermal Engines University of the Basque Country (UPV / EHU) Engineer Torres Quevedo Square 1 48013 Bilbao BI Spain Doctoral Program in Engineering of Materials and Sustainable Processes University of the Basque Country UPV/EHU 48013 Bilbao Spain

This work aims to describe the construction of a low-cost functional prototype of an electromechanical hand with opening and closing capacity. The device, built on an ABS filament extruder, is actuated by a MG995 high torque servo motor, controlled by an Arduino-UNO R3 board, from the processing of electromyographic signals carried out by: MyoWare Muscle Sensor. The realization and functional evaluation of the device is developed in six phases: The first is to select the thermo-deformable materials, the second is to select the electronic components; the third phase is the design of the electromechanical hand prosthesis, the fourth phase was the construction of the mechanical parts; the fifth phase is the development of the control program on the electronic card; and the sixth phase of the project consists of validating the developed prototype by observing its opening and closing through the oscilloscope. Due to the low cost of development and ease of reproducibility (because it is built under the open-source philosophy), this work is expected to make a contribution to the disabled community, especially the one with limited resources.

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Development of A Station for The Measurement of Environmental Conditions in The Unidades Tecnologicas De Santander (UTS), Using Telemetry and Database Management with Raspberry Pi

引用

IOP Conference Series: Materials Science and engineering 2021年第1期1154卷

作者： A Quintero Ruiz C L Sandoval-Rodriguez A D Rincon-Quintero B E Tarazona-Romero C G Cárdenas-Arias J G Ascanio-Villabona Energy Systems Automation and Control Research Group (GISEAC) Design and materials research group (DIMAT) Electromechanical Engineering Faculty of Natural Sciences and Engineering Unidades Tecnologicas de Santander (UTS) Road No 9-82 students 680005 Bucaramanga Colombia Doctoral Program in Electronic and Communications Department of Communications Engineering University of the Basque Country UPV/EHU 48013 Bilbao Spain Doctoral Program in Energy Efficiency and Sustainability in Engineering and Architecture Department of Machines and Thermal Engines University of the Basque Country (UPV / EHU) Engineer Torres Quevedo Square 1 48013 Bilbao BI Spain Doctoral Program in Engineering of Materials and Sustainable Processes University of the Basque Country UPV/EHU 48013 Bilbao Spain

This article focuses on the development of an electronic remote data acquisition system which will have the following sensors adapted: thermometer, hygrometer and barometer. From the measurements of these will be obtained data of temperature, relative humidity, atmospheric pressure, which will be stored in the form of records in a data recorder using Raspberry Pi and through wireless communication the data will be transmitted when the software requires it to a module Central of visualization, which according to some parameters will automatically update the histories according to the defined times, or at the request of the user. It will be implemented following a process of research, planning, execution and validation. It implies the necessary information for the implementation, in the planning process the different systems to be used will be divided into 3 groups, measurement and registration system, communication system and a control system composed of the software, and then the acquisition will proceed of the equipment and accessories necessary to execute the assembly. In the execution process, the physical implementation of all the systems will be carried out and the programming of the data acquisition, communication and data storage systems will be developed.

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Modal regression based structured low-rank matrix recovery for multi-view learning

arXiv

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arXiv 2020年

作者： Xu, Jiamiao Wang, Fangzhao Peng, Qinmu You, Xinge Wang, Shuo Jing, Xiao-Yuan Philip Chen, C.L. School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute China State Key Laboratory of Software Engineering School of Computer Wuhan University China Department of Computer and Information Science Faculty of Science and Technology University of Macau 99999 China Dalian Maritime University Dalian116026 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Low-rank Multi-view Subspace Learning (LMvSL) has shown great potential in cross-view classification in recent years. Despite their empirical success, existing LMvSL based methods are incapable of well handling view discrepancy and discriminancy simultaneously, which thus leads to the performance degradation when there is a large discrepancy among multi-view data. To circumvent this drawback, motivated by the block-diagonal representation learning, we propose Structured Low-rank Matrix Recovery (SLMR), a unique method of effectively removing view discrepancy and improving discriminancy through the recovery of structured low-rank matrix. Furthermore, recent low-rank modeling provides a satisfactory solution to address data contaminated by predefined assumptions of noise distribution, such as Gaussian or Laplacian distribution. However, these models are not practical since complicated noise in practice may violate those assumptions and the distribution is generally unknown in advance. To alleviate such limitation, modal regression is elegantly incorporated into the framework of SLMR (term it MR-SLMR). Different from previous LMvSL based methods, our MR-SLMR can handle any zero-mode noise variable that contains a wide range of noise, such as Gaussian noise, random noise and outliers. The alternating direction method of multipliers (ADMM) framework and half-quadratic theory are used to efficiently optimize MR-SLMR. Experimental results on four public databases demonstrate the superiority of MR-SLMR and its robustness to complicated noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

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Electrical bioimpedance spectroscopy as a tool for non-destructive monitoring nitrogen supply in two lettuce genotypes

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Scientia Horticulturae 2025年 349卷

作者： Flórián Kovács Ákos Odry Zoltán Vizvári Anita Szegő Haimei Chen Enikő Papdi Ingrid Melinda Gyalai Ágnes Kun Péter Odry Katalin Juhos Department of Agro-Environmental Studies Hungarian University of Agriculture and Life Sciences Villányi str. 29-43 Budapest H-1118 Hungary Faculty of Agriculture Institute of Plant Sciences and Environmental Protection University of Szeged Hódmezővásárhely 6800 Hungary Department of Mechatronics and Automation Faculty of Engineering University of Szeged Moszkvai krt. 9 Szeged 6725 Hungary Department of Control Engineering and Information Technology University of Dunaújváros Táncsics Mihály u. 1 Dunaújváros 2400 Hungary John Von Neumann Faculty of Informatics Biomatics and Applied Artificial Intelligence Institute Óbuda University Bécsi str. 96 Budapest H-1034 Hungary Bioimpedance Technologies Research Center University Research and Innovation Center Óbuda University Bécsi str. 96 Budapest H-1034 Hungary Multidisciplinary Medical and Engineering Cellular Bioimpedance Research Group Szentagothai Research Centre University of Pecs Ifjusag str. 20 Pecs H-7624 Hungary Department of Plant Physiology and Plant Ecology Institute of Agronomy Hungarian University of Agriculture and Life Sciences Ménesi Str. 44 Budapest H-1118 Hungary Department of Floriculture and Dendrology Urban Planning and Garden Art Institute of Landscapes Architecture Hungarian University of Agriculture and Life Sciences Villányi ut 29-43 Budapest 1118 Hungary Research Center for Irrigation and Water Management Institute of Environmental Sciences Hungarian University of Agriculture and Life Sciences Anna-Liget str. 35. Szarvas H-5540 Hungary

Accurate monitoring of nutrient supply is crucial for effective plant nutrition management. This study introduces a bioimpedance spectroscopy (BIS) approach to evaluate how lettuce genotypes respond to nitrogen (N) supply, illuminating the link between BIS and N metabolism. The research consisted of two parts: a preliminary experiment focusing on extracellular fluid resistance, followed by a second experiment involving five different N treatments applied to two lettuce genotypes. BIS spectra were recorded from 1 Hz to 100 kHz, with a total of 224 measurements. Plant physiological analyses assessed total and extracellular fluid nitrate (NO 3 − ) concentrations, pigment concentration, total N content, and cell membrane stability index. In the preliminary experiment, a significant negative correlation was observed between extracellular fluid NO 3 − concentration and extracellular fluid resistance (r = – 0.67). Furthermore, the frequency range around 63 Hz (R 2 = 0.97) appeared most sensitive to NO 3 − dynamics in the ‘Kobak’ lettuce genotype. In the two lettuce genotypes exposed to the five different N treatments, extracellular fluid resistance negatively correlated with total N and NO 3 − content ( r = – 0.76 and – 0.73), while vacuole fluid resistance showed a moderate correlation ( r = – 0.51). Cell membrane capacitance was also significantly correlated with membrane stability index ( r = 0.68), indicating that low-N conditions reduce membrane charge storage. However, these correlations appeared highly genotype dependent. Heatmap-based hierarchical clustering of Z-score standardized BIS parameters further confirmed these genotype-specific patterns. Collectively, these findings suggest that BIS captures key aspects of N uptake and storage, particularly in the extracellular fluid compartment. Overall, BIS offers a robust, non-destructive method for monitoring N status and may enhance precision in nutrient management for lettuce and other crops, although the genotype-s

关键词： Extracellular fluid resistance Vacuole fluid resistance Cell membrane capacitance Nitrogen uptake

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