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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Cui Wei Ye-Hwa Chen Yanling Wei Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Key Laboratory of Measurement and Control of Complex System of Engineering School of Automation Southeast University Nanjing China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strategy unfolds in two phases: initially, a nominal control scheme is devised neglecting uncertainty and deviations in initial conditions from constraints. Subsequently, uncertainty is categorized into matched and mismatched components, ensuring that mismatched uncertainties remain unobservable. Leveraging the structural characteristics of the uncertainty bound, a novel segmented adaptive law is proposed and seamlessly integrated into the adaptive robust control framework. By employing the Lyapunov minimax approach, the method ensures uniform boundedness and uniform ultimate boundedness simultaneously, thereby ensuring approximate adherence to constraints for underactuated mechanical systems facing both matched and mismatched uncertainties alongside initial condition deviations.

关键词： Robust control Uncertainty Adaptive systems Costs Automation Nonlinear dynamical systems Mechanical systems Closed loop systems Robots

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Effective Methods to Improve the Accuracy of False Light Source Recognition in Visible Light Indoor Positioning

Effective Methods to Improve the Accuracy of False Light Sou...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： DeYue Zou LinNa Yan Siyu Gao Yunfeng Liu School of Information and Communication Engineering Dalian University of Technology Dalian China School of Intelligence & Electronic Engineering Dalian Neusoft University of Information Dalian China Beijing Institute of Control and Electronic Technology Dalian China

ISBN: (数字)9798350366402

ISBN: (纸本)9798350366419

With the development of visible light communication technology, visible light indoor positioning technology has become one of the research hotspots in indoor positioning technology. Visible light indoor positioning uses the light source information in the scene to locate the receiving end. However, the indoor environment is complex, and there are likely to be mirrors, glass and other reflective objects. These objects reflect to generate a pseudo-light source that transmits information similar to the actual light source, affecting the positioning result. Aiming at the recognition of pseudo-light sources, this paper adds classification steps to the algorithm based on chiral light source array, and proposes two methods that can improve the accuracy of identifying true and false light sources: K-Nearest Neighbor (KNN) classification and Weighted K-Nearest Neighbor (WKNN) classification and correction. Based on the chiral detection algorithm of vector product, we compare the success rates of the improved methods with the algorithm without the improved methods. The simulation results show that the accuracy of false detection can be further improved by adding the improved method, so as to improve the positioning accuracy.

关键词： Accuracy Simulation Indoor navigation Nearest neighbor methods Vectors Classification algorithms Reliability Mirrors Light sources Visible light communication

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Solar Radiation Forecasting Based on Random Forest and XGBoost 7

Solar Radiation Forecasting Based on Random Forest and XGBoo...

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7th International Conference on Green technology and Sustainable Development, GTSD 2024

作者： Nguyen, Nhat-Truong Tuong Dao, Thai Cat Tuyen Nguyen, Le Nhut Nguyen, Thanh-Dat Le, Minh-Vuong French, Isobel Timothea Doan, Van-Tuong Kim Vo, Van Hoang Tran, Nghi C. Pham, Duc-Hung Nguyen, Van-Trung Ho Chi Minh City University of Technology and Education Department of Renewable Energy Viet Nam Ho Chi Minh City Industry and Trade College Department of Control Engineering and Automation Viet Nam LILAMA2 International Technology College Dongnai Viet Nam Institute of Cognitive Neuroscience National Central University Taiwan College of Information and Communication Technology Can Tho University Viet Nam Hung Yen University of Technology and Education Faculty Electrical and Electronic Engineering Viet Nam

ISBN: (纸本)9798350386073

Renewable energy offers a viable alternative to depleting fossil fuels, contributing to global warming and greenhouse gas emissions. Thus, solar energy is widely favored as a renewable energy source. However, the output power of solar systems is unstable and is highly dependent on environmental circumstances such as radiation, humidity, temperature, and wind. Therefore, accurately estimating solar radiation is crucial for successful integration of the solar system into existing electrical grid systems. In this study, two different machine learning models, XGBoost and Random Forest, were used to predict solar radiation data in Ho Chi Minh City, Vietnam. The results show that RMSE and MAE of the Random Forest model (61.09 and 24.37) is smaller compared to XGBoost (61.31 and 25.08). Regression value of the two models is close to 0.955. In summary, this paper demonstrates that these two machine learning algorithms effectively forecast solar radiation, with the Random Forest model showing better performance. © 2024 IEEE.

关键词： Solar irradiance

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Optimizing Performance in Automatic Powder Filling Systems

Optimizing Performance in Automatic Powder Filling Systems

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International Conference on Power, Energy, control and Transmission Systems (ICPECTS)

作者： Mohanraj K Ramesh A K.S. Vairavel Mohammed Thoufik S Muthuraja R Mohamed Arshad M Department of Instrumentation & Control Engineering Sri Sairam Engineering College Chennai India Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore India Electronics and Instrumentation Engineering Bannari Amman Institute of Technology

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

There have been crucial changes in the packaging industry recently, especially with regard to Form Fill and Seal (FFS) machines. These machines can be found in different sizes making them available for use by small businesses that want to lower their plant costs using inexpensive automated packaging solutions. This paper describes a low-cost weighing and pouring mechanism for improving accuracy of pouch filling machine. The process flow is carefully designed so as to achieve optimum production rates. Manipulators under the control of our mechatronics system are regulated through feedback from sensors managed by microcontroller.

关键词： Industries Mechatronics Costs Automation Seals Packaging Filling Sensor systems Sensors Safety

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Low-carbon economic dispatch of integrated energy system with carbon capture power plant and multiple utilization of hydrogen energy

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Frontiers in Energy Research 2024年 12卷

作者： Wang, Jiarui Ji, Xiu Meng, Xiangdong Bai, Yang Li, Meiyue State Grid Jilin Electric Power Co. Ltd. Changchun China National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control with Safety Operation Technology Changchun Institute of Technology Changchun China

In the context of "dual carbon", in order to promote the consumption of renewable energy and improve energy utilization efficiency, a low-carbon economic dispatch model of an integrated energy system containing carbon capture power plants and multiple utilization of hydrogen energy is proposed. First, introduce liquid storage tanks to transform traditional carbon capture power plants, and at the same time build a multi-functional hydrogen utilization structure including two-stage power-to-gas, hydrogen fuel cells, hydrogen storage tanks, and hydrogen-doped cogeneration to fully exploit hydrogen. It can utilize the potential of collaborative operation with carbon capture power plants;on this basis, consider the transferability and substitutability characteristics of electric heating gas load, and construct an electric heating gas comprehensive demand response model;secondly, consider the mutual recognition relationship between carbon quotas and green certificates, Propose a green certificate-carbon trading mechanism;finally establish an integrated energy system with the optimization goal of minimizing the sum of energy purchase cost, demand response compensation cost, wind curtailment cost, carbon storage cost, carbon purchase cost, carbon trading cost and green certificate trading compensation. Optimize scheduling model. The results show that the proposed model can effectively reduce the total system cost and carbon emissions, improve clean energy consumption and energy utilization, and has significant economical and low-carbon properties. Copyright © 2025 Wang, Ji, Meng, Bai and Li.

关键词： Carbon capture and storage

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Analysis of human-footbridge-MTMD coupled system and MTMD optimization design based on the pseudo-excitation method

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Zhendong Gongcheng Xuebao/Journal of Vibration engineering 2025年第4期38卷 794-802页

作者： Wen, Jinlong Li, Yang Wang, Zhihao Chen, Aijiu Hu, Mingyi College of Civil Engineering and Communication North China University of Water Resources and Electric Power Zhengzhou450045 China Faculty of Civil Engineering and Mechanics Kunming University of Science and Technology Kunming650000 China Henan Engineering Research Center for Structural Vibration Control and Health Monitoring Zhengzhou450045 China Engineering Vibration Control Technology Research Center State Machinery Group Science and Technology Research Institute Co. Ltd. Beijing100083 China

To establish the optimal design method of multiple tuned mass damper（MTMD）for the footbridge considering the vertical human-structure interaction，the parameters randomness of the mass-spring-damper（MSD）pedestrian model is simulated，and the vertical dynamic response of the random crowd-footbridge-MTMD system is calculated based on the pseudo-excitation method. Then，the effect of vertical human-structure interaction on the dynamic response of the footbridge-TMD system is demonstrated. Finally，based on the H2 performance of the acceleration transfer function and response surface methodology of the coupled system，an optimal design method of MTMD for footbridge vibration control considering vertical human-structure interaction is established. The results show that the dynamic response calculation method of the coupled system avoids a large number of nonlinear time history analyses，and the power spectrum and root mean square of the coupled system response can be obtained efficiently. The vertical human-structure interaction makes the TMD detuning effect significant，and the reduction rate of TMD with 3% mass ratio decreases by 37.19% when the crowd density increases from 0.25 person/m2 to 1.25 person/m2. The proposed MTMD optimization design method for footbridge has an average mitigation rate of over 70% for footbridge acceleration response. © 2025 Nanjing University of Aeronautics an Astronautics. All rights reserved.

关键词： Dynamic response

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Grip strength forecast and rehabilitative guidance based on adaptive neural fuzzy inference system using sEMG

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Personal and Ubiquitous Computing 2022年第4期26卷 1215-1224页

作者： Jiang, Du Li, Gongfa Sun, Ying Kong, Jianyi Tao, Bo Chen, Disi Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Institute of Precision Manufacturing Wuhan University of Science and Technology Wuhan University of Science and Technology Wuhan430081 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom

In order to resolve the problem of unstable control of force in human–computer interaction based on surface EMG signals, the adaptive neural fuzzy inference system is designed to achieve the grip strength assessment. As we know, the acquisition of surface EMG signal is non-invasive, which provides a better evaluation index for rehabilitation training in the medical process. By establishing the relationship between grip force and surface electromechanical signals, the effect of rehabilitation training can be evaluated directly while reducing the types of sensors used. Firstly, the experimental equipment are introduced, which are utilized to carry out simultaneous acquisition of surface EMG signals and forces. Then, the traditional features of sEMG and the corresponding algorithms are illustrated, based on this, supplementing the energy eigenvalue with wavelet analysis and fuzzy entropy. In which, fuzzy entropy is effective in characterizing muscle fatigue that can effectively reduce the impact of muscle fatigue on force assessment. Finally, combining fuzzy logic implication and neural network, the adaptive neural fuzzy inference system is designed, which is trained by extracted feature vectors. The experimental result shows the method used in this paper can effectively predict the grip force. Further, force prediction based on sEMG can be used to guide rehabilitation therapy in virtual space, combined with an electrical stimulator. © 2019, Springer-Verlag London Ltd., part of Springer Nature.

关键词： Eigenvalues and eigenfunctions

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Research on Early Warning Algorithm of Active Distribution Network Operational Risk Based on Improved Apriori Association Rules

Research on Early Warning Algorithm of Active Distribution N...

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2021 China Automation Congress, CAC 2021

作者： Ji, Xiu Li, Dianwen Tian, Xin Hou, Yiwei Meng, Xiangping Changchun Institute of Technology National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control with Safety Operation Technology Changchun China Changchun University of Technology National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control with Safety Operation Technology Changchun China

ISBN: (纸本)9781665426473

In order to improve the accuracy and rapidity of risk early warning of active distribution network, this paper adopts the idea of data mining and proposes an improved Apriori algorithm for early warning of risks in the distribution network. This method takes weather, risk equipment and risk reasons as the research objects, and through mathematical analysis, proposes an improved Apriori algorithm based on seasonal classification, which greatly improves the efficiency of the algorithm, thus improving the response speed of the risk early warning system. At the same time, a failure mode library of typical environmental scenarios has been established, and enumerate the algorithm flow. The display interface of the system is designed and developed, so that the matching information is displayed in a separate display interface. Through the example analysis, not only the feasibility of the algorithm is verified, but also the readability of the risk warning data is improved, which has a guiding significance for the actual engineering construction. © 2021 IEEE

关键词： Learning algorithms

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A Semi-Supervised Method Using Cycle Consistency and Multi-Perspective Dilated for Sar-to-Optical Translation

SSRN

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SSRN 2024年

作者： Wang, Jinyu Yang, Haitao Liu, Zhengjun Chen, Hang Department of Space Equipment The Academy of Equipment Beijing101416 China Department of Automation Measurement and Control Harbin Institute of Technology Harbin150001 China Space Engineering University China

Synthetic Aperture Radar (SAR) is a powerful imaging sensor capable of operating in any weather and at any time, despite its image interpretation poses challenges. Translating SAR images to optical (S2O) can serve as a beneficial supplement for target detection, image alignment, and image fusion. The existing S2O translation employs solely unsupervised or supervised techniques. However, the supervised method requires a substantial quantity of aligned data support, while the unsupervised method fails to guarantee the quality of image generation. This research presents a novel semi-supervised S2O generating approach that can obtain domain-level and pixel-level mapping relationships. A dual-branch cycle consistency loss has been developed to independently constrain supervised and unsupervised modules. To improve global and sparsity feature extraction, the generator combines sliding dilated convolution with multi-respective parallel branching. Using just 1100 pairs of training sets, extensive experiments have demonstrated that the suggested strategy outperforms baseline methods in both subjective and objective standards. Where FID is optimized by 23.41%, 49.25%, 48.57%, 16.73%, and 42.32% on the five land classes. © 2024, The Authors. All rights reserved.

关键词： Radar imaging

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Design and Implementation of Indoor Visual Autonomous Navigation System for Quadrotor UAV Based on Binocular Camera and IMU

Design and Implementation of Indoor Visual Autonomous Naviga...

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Computer Science, Electronic Information engineering and Intelligent control technology (CEI), IEEE International Conference on

作者： Jiaze Tang Tianxing Guo Liudan Junbao Li Jinwei Sun Wenbin Huang Qisong Wang Electrical Measurement technology and Intelligent Control Institute School of Instrumention Science and Engineering Harbin Institute of Technology Harbin China Schools of electronics and information Engineering Harbin Institute of Technology Harbin China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (数字)9798350372052

ISBN: (纸本)9798350372069

Addressing the challenge of unmanned aerial vehicles (UAVs) navigating indoors without satellite positioning, this study introduces a novel method combining binocular camera and inertial measurement unit (IMU) data. This approach overcomes the structural differences between visual and inertial information, integrating them effectively for enhanced indoor autonomous navigation. The research presents a gradient-free path planning framework, pivotal for enhancing the UAV's ability to execute efficient and stable flight in intricate indoor settings. The cornerstone of this system is an advanced path planning algorithm, adept at swiftly identifying optimal routes and adapting to environmental shifts. The system's efficacy was rigorously evaluated through simulations and real-world tests, confirming its precision in positioning and path planning without reliance on satellite data. The findings demonstrate the system's capacity for precise localization and effective route determination, utilizing an integration of visual and inertial inputs. This research significantly contributes to the autonomous flight capabilities of UAVs, offering a valuable reference for future UAV autonomous navigation systems. By delving into visual-inertial fusion navigation technology, the study paves the way for expanded indoor UAV applications.

关键词： Visualization Satellites measurement units Inertial navigation Autonomous aerial vehicles Satellite navigation systems Path planning

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