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12th International Conference on Information Technology and electrical engineering, ICITEE 2020

作者： Tamba, Tua A. Nazaruddin, Yul Y. Parahyangan Catholic University Center for Control Automation Systems Engineering Department of Electrical Engineering Bandung Indonesia Institut Teknologi Bandung Instrumentation Control Research Group Indonesia

ISBN: (纸本)9781728110974

One important task in the deployment of a wireless sensor network is solving the sensor network localization problem to assure location awareness of each sensor node in the network. The sensor network localization can be formulated as a global optimization problem that aims to minimize the squared inter-sensor distances under the constraint that such distances equal to some given numbers. The corresponding optimization formulation is generally nonsmooth, nonconvex, and NP-hard problem, and thus prior works have proposed approximate solution using relaxation methods such as semidefinite or conic programming. In this paper, a linear programming relaxation approach is proposed to solve such an optimization problem using the concept of Handelman's representation of nonnegative polynomial functions over polytopic set. Numerical simulation results are given to illustrate the promising potential of the proposed approach. © 2020 IEEE.

关键词： Linear programming

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A novel algorithm for optimizing bundle adjustment in image sequence alignment

arXiv

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arXiv 2024年

作者： Xu, Hailin Wang, Hongxia Han, Renmin Zhang, Huanshui College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China School of Control Science and Engineering Shandong University Shandong Jinan250061 China Research Center for Mathematics and interdisciplinary Sciences Shandong University Qingdao266237 China College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao266590 China

The Bundle Adjustment (BA) model is commonly optimized using a nonlinear least squares method, with the Levenberg-Marquardt (L-M) algorithm being a typical choice. However, despite the L-M algorithm’s effectiveness, its sensitivity to initial conditions often results in slower convergence when applied to poorly conditioned datasets, motivating the exploration of alternative optimization strategies. This paper introduces a novel algorithm for optimizing the BA model in the context of image sequence alignment for cryo-electron tomography, utilizing optimal control theory to directly optimize general nonlinear functions. The proposed Optimal control Algorithm (OCA) exhibits superior convergence rates and effectively mitigates the oscillatory behavior frequently observed in L-M algorithm. Extensive experiments on both synthetic and real-world datasets were conducted to evaluate the algorithm’s performance. The results demonstrate that the OCA achieves faster convergence compared to the L-M algorithm. Moreover, the incorporation of a bisection-based update procedure significantly enhances the OCA’s performance, particularly in poorly initialized datasets. These findings indicate that the OCA can substantially improve the efficiency of 3D reconstructions in cryo-electron tomography. © 2024, CC BY.

关键词： Least squares approximations

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Position control of X-Y Precision Planar Motion Stage Based on Iterative Learning and Cross-coupling

Position Control of X-Y Precision Planar Motion Stage Based ...

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Data Driven control and Learning systems (DDCLS)

作者： Jingzhe Fang Tao Zhang Xiyou Chen Chen Qi Guopeng Zhang Hualiang Zhang Hongyu Yan School of Electrical Engineering Shenyang University of Technology Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Dalian University of Technology Dalian China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

In some precision machining applications, not only should we pay attention to the tracking accuracy of the X-Y precision plane motion table, but the more important criterion is the contour accuracy. This paper proposes an adaptive iterative learning control that adjusts in real time with the system's working state for the X-Y precision plane motion stage control system. Then on the basis of adaptive iterative learning control, the relationship between the two axes is established by cross-coupling control, the contour error of the system is calculated in real time, and the stability of the system is improved. The final experimental results show that the improved algorithm has smaller contour error and better robustness.

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Real-time Hybrid Gait Phase Recognition Algorithm Under Continuous Multimodal Locomotion for Lower Limb Exoskeleton

Real-time Hybrid Gait Phase Recognition Algorithm Under Cont...

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2022 CSAA/IET International Conference on Aircraft Utility systems, AUS 2022

作者： Miao, Yinan Wang, Xingjian Wang, Jiaqi Wang, Shaoping Gavrilov, Alexander I. School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Qingdao Research Institute Beihang University Qingdao266104 China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang University Beijing100191 China Bauman Moscow State Technical University Department of Automatic Control Systems Moscow105005 Russia

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

Nowadays, exoskeletons' ability to operate in complex environments is increasingly important. It is challenging to obtain an accurate gait phase under continuous multimodal locomotion. A hybrid gait phase recognition algorithm is proposed combining the adaptive-oscillator-based algorithm and the model-based algorithm. The modification law is adopted to make two algorithms amend each other reciprocally. The design of the modification law combines the advantages of oscillator-based algorithms and model-based algorithms. The gait phase estimation results are more accurate via the hybrid gait phase prediction algorithm (GPRA). Therefore, appropriate assistance actuation and higher efficiency are obtained under the complicated multimodal locomotion. An experiment was designed to verify the performance of the hybrid GPRA. As a result, the hybrid GPRA can still produce a high-precision gait phase with low latency even when the locomotion mode switches. The hybrid GPRA can provide accurate gait phase and assistance timing under continuous multimodal locomotion. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Exoskeleton (Robotics)

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High Real-time Locomotion Recognition Algorithm Using Inertial Measurement Units

High Real-time Locomotion Recognition Algorithm Using Inerti...

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2022 CSAA/IET International Conference on Aircraft Utility systems, AUS 2022

作者： Wang, Jiaqi Wang, Xingjian Miao, Yinan Wang, Shaoping An, Mailing Miao, Yiqi Gavrilov, Alexander I. School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Qingdao Research Institute Beihang University Qingdao266104 China Beijing Advanced Innovation Center for Big Data-based Precision Medicine Beihang University Beijing100191 China Bauman Moscow State Technical University Department of Automatic Control Systems Moscow105005 Russia

ISBN: (数字)9781839537769

ISBN: (纸本)9781839537769

Human-machine interaction devices (HMI), such as assisted exoskeletons and assisted prostheses, that improve human motion behaviours are playing an increasingly important role in various fields. In order for these HMI devices to provide accurate and appropriate assistance to wearers, the real-time recognition of locomotion with accuracy is among the key issues to be solved. This paper proposes a high real-time motion pattern recognition algorithm using inertial measurement units (IMU) that can accurately and quickly identify the current motion state by collecting various motion parameters of the lower limb during human walking. The algorithm uses a trajectory solving and motion direction discrimination method based on the shank zero velocity point and a terrain classification method based on an F-score improved support vector machine (F-score-SVM). In this paper, experimental data was used to verify the performance of the algorithm. Results show that the algorithm performs better than traditional recognition algorithms in complex environments. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Support vector machines

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Path-tracking of Mobile Robot Using PD-type Iterative Learning control with Forgetting Factor

Path-tracking of Mobile Robot Using PD-type Iterative Learni...

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Chinese control and Decision Conference, CCDC

作者： Tao Zhang Jingzhe Fang Yun Teng Xintong Wang Yiqiang Zhang Xiyou Chen School of Electrical Engineering Dalian University of Technology Dalian China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China

In this paper, a discrete iterative learning control strategy is proposed for the path-tracking problem of mobile robot trajectory tracking with repeated trajectories. The algorithm adds the forgetting factor to the PD-type discrete iterative learning control and considers the correction of the initial state of the control. The convergence of the algorithm is proved rigorously by using the paradigm theory, and the sufficient conditions of the paradigm form to make the algorithm converge are obtained. Finally, the effectiveness of the proposed algorithm is verified by simulation.

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Fast Realization of Robot 3D Simulation Based on WebGL

Fast Realization of Robot 3D Simulation Based on WebGL

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Chinese control and Decision Conference, CCDC

作者： Tao Zhang Xintong Wang Yun Teng Jingzhe Fang Yiqiang Zhang Xiyou Chen School of Electrical Engineering Dalian University of Technology Dalian China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China

As science and technology have advanced, an increasing number of people are focusing their study on 3D robot simulation. The 3D quick simulation of the mechanical arm can be achieved using 3D modeling software and ***. Use the third-party WebGL library *** [1] to construct the simulation scenario, then interact with and render the 3D scene and 3D robot model directly on the Web, which is easier and faster than downloading plug-ins [2] . This essay briefly explains the benefits and applicability of *** in the creation of 3D virtual simulations, then goes on to discuss the quick implementation process of 3D robot simulations before summarizing the building technique.

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Multimodal Emotion Recognition Based on Multi-Scale Facial Features and Cross-Modal Attention 26

Multimodal Emotion Recognition Based on Multi-Scale Facial F...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Bao, Chengao Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Tokyo Institute of Technology Yokohama226-8502 Japan Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798331521950

A multi-modal emotion recognition method based on facial multi-scale features and cross-modal attention (MS-FCA) network is proposed. The MSFCA model improves the traditional single-branch ViT network into a two-branch ViT architecture by using classification tokens in each branch to interact with picture embeddings in the other branch, which facilitates effective interactions between different scales of information. Subsequently, audio features are extracted using ResNet18 network. The cross-modal attention mechanism is used to obtain the weight matrices between different modal features, making full use of inter-modal correlation and effectively fusing visual and audio features for more accurate emotion recognition. Two datasets are used for the experiments: eNTERFACE'05 and REDVESS dataset. The experimental results show that the accuracy of the proposed method on the eNTERFACE'05 and REDVESS datasets is 85.42% and 83.84% respectively, which proves the effectiveness of the proposed method. © 2025 IEEE.

关键词： Modal analysis

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Modulated-Virtual-Vector-Based Predictive Current control for Dual Three-Phase PMSM With Enhanced Steady-State Performance

Modulated-Virtual-Vector-Based Predictive Current Control fo...

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Annual Conference of Industrial Electronics Society

作者： Ze Li Xingyu Zheng Jinhui Xia Liling Wang Yuanbo Guo Xiaonan Gao Zhiheng Liu Xiaohua Zhang College of Electronic and Information Engineering Hebei University Baoding China School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering (Southeast University) Ministry of Education Southeast University Nanjing China School of Electrical Engineering Dalian University of Technology Dalian China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden The School of Electrical Engineering Dalian University of Technology Dalian China

Dual three-phase permanent magnet synchronous machine (DTP-PMSM) has attracted great attention due to its high reliability and high-power output capacities. However, the conventional single-voltage-vector-based predictive current control (SV-PCC) for DTP-PMSM presents high torque ripple and current harmonics, and high computational burden. To solve those issues, a modulated-virtual-vector-based PCC (MVV-PCC) for DTP-PMSM is proposed in this paper. Wherein, twenty-four VVs are synthesized by the inherent voltage vectors, and two VVs and one zero voltage vector with optimal duty cycles are determined and applied in each sampling period to improve the steady-state performance. The selection of optimal VVs and the calculation of the optimal duty cycles are simplified by integrating the deadbeat control and modulation scheme. Various comparisons are carried out to validate the effectiveness and superiority of the proposed MVV-PCC strategy.

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A Multiple Ant Colony System for the Electric Vehicle Routing Problem with Time Windows

A Multiple Ant Colony System for the Electric Vehicle Routin...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Michalis Mavrovouniotis Georgios Ellinas Changhe Li Marios Polycarpou Department of Electrical and Computer Engineering KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781665487696

Ant colony optimization (ACO) has been found to be useful on several vehicle routing problem variations. In this work, ACO is applied to the electric vehicle routing problem with time windows (E-VRPTW). The E-VRPTW has a hierarchical multiple objective function, which is to minimize the number of electric vehicles and the total distance traveled. A multiple ACO is applied to E-VRPTW in which two colonies cooperate to minimize the objectives in parallel. A local search is embedded in ACO to improve the quality of the output. The experimental results on a set of benchmark instances show that the multiple ACO is competitive with existing methods.

关键词： Ant colony optimization Vehicle routing Benchmark testing Electric vehicles Routing Search problems Linear programming

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