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17th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2024

作者： Han, Chunxiao Zhang, Jingyan Jia, Yuyu Che, Yanqiu Tianjin Key Laboratory of Information Sensing & Intelligent Control China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin 300222 China

ISBN: (纸本)9798331507398

Brain-controlled system has been used in assisting disabilities, and how to enable such groups to have the ability to communicate with the surroundings has become the focus of research. However, due to the individual differences and the dynamic time-varying brain states, the fixed time window used in the traditional Filter Bank Canonical Correlation Analysis (FBCCA) algorithm for Steady-State Visual Evoked Potential-based Brain-Computer Interface (SSVEP-BCI) is not optimal, which limits its generalizability. Therefore, in this paper, based on the SSVEP experimental paradigm, we propose an improved FBCCA algorithm with dynamic window based on the difference level between correlation coefficients. Compared with the traditional FBCCA algorithm, the accuracy is significantly improved. Furthermore, this paper designs a BCI-based robotic arm control system, achieving real-time and precise object grasping. This validates the feasibility and effectiveness of the proposed algorithm. Our findings may provide a theoretical basis and technical support for the practical application of BCI. © 2024 IEEE.

关键词： Robotic arms

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End-point Steady control for Whole-Body control Mobile Manipulators by Null Space Tunation 8

End-point Steady Control for Whole-Body Control Mobile Manip...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Zhang, Enjin Gan, Yahui Dai, Xianzhong School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China

ISBN: (纸本)9798350300178

This paper deal with the end-point steady control problem of a mobile manipulators(MM) at the velocity level. Mobile manipulators are usually kinematically redundant when performing tasks, so multiple subtasks can be performed simultaneously, such as tracking the trajectory of the end effector(EE), optimizing manipulability, etc. First, the mobile manipulators system is modeled as an ordinary jointed manipulator. The velocity of the EE has a higher priority, scheduling low-priority tasks in the null space of high-priority tasks leaves high-priority tasks unaffected. The damped least square method is used to generate a kinematic inverse solution with singular robustness, and the gradient projection method is used to optimize the manipulability measure. By analyzing the structure of the Jacobian matrix, the complexity of gradient calculation is reduced. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments. © 2023 IEEE.

关键词： Jacobian matrices

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An Online Strategy for Nonlinear Vector Autoregression 7

An Online Strategy for Nonlinear Vector Autoregression

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7th International Conference on Robotics, control and automation engineering, RCAE 2024

作者： Fang, Gang Liu, Yiqi South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science & Engineering Guangzhou510640 China

ISBN: (纸本)9798350355642

Nonlinear vector autoregression (NVAR), as an effective alternative to traditional reservoir computing (RC), has garnered significant attention in the field of time series prediction in recent years. Unlike conventional RC, NVAR does not require the use of random sampling matrices to define the underlying recurrent neural network, and it features fewer hyperparameters. However, NVAR is an offline model, making it challenging to meet the real-time monitoring requirements of industrial processes. Inspired by the Woodbury matrix identity, this paper proposes an online NVAR that can update the model using data arriving in blocks. Subsequently, this study constructs a soft sensing model based on the online NVAR to perform real-time monitoring of industrial processes. Finally, the effectiveness of the proposed method is validated using a real-world dataset from a wastewater treatment plant. © 2024 IEEE.

关键词： Wastewater treatment

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Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1458-1475页

作者： Jing Liang Hongyu Lin Caitong Yue Ponnuthurai Nagaratnam Suganthan Yaonan Wang School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001 School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China KINDI Center for Computing Research Qatar UniversityDohaQatarand also with the Nanyang Technology UniversitySingapore College of Electrical and Information Engineering and also with the National Engineering Research Center for Robot Visual Perception and Control TechnologyHunan UniversityChangsha 410082China IEEE

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective *** paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision *** to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal *** proposed algorithm adopts a dual-population framework and an improved environmental selection *** utilizes a convergence archive to help the first population improve the quality of *** improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first *** combination of these two strategies helps to effectively balance and enhance conver-gence and diversity *** addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is *** proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

关键词： Benchmark functions diversity measure evolution-ary algorithms multimodal multiobjective optimization.

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An Improved Hunger Games Search Algorithm-based Multi-peak MPPT control for PV System under Partial Shading

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Recent Patents on Mechanical engineering 2023年第4期16卷 261-273页

作者： Yi, Lingzhi Ma, Hao Wang, Yahui Liu, Jiangyong Shi, Hao Cheng, Siyue College of Automation and Electronic Engineering Xiangtan University Hunan Xiangtan411105 China Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan411105 China College of Electrical and Information Engineering Hunan University Hunan Changsha410082 China

Background: In photovoltaic power generation systems, partial shading may cause the PV array to mismatch, thus leading to multi-peak output characteristics, which makes the conventional Maximum Power Point Tracking (MPPT) algorithm easily fall into local extremes and cause power loss. Objective: The study aimed to accurately and quickly track the maximum power point of PV arrays in partial shading through swarm intelligence algorithms. Methods: Based on the above, a MPPT control algorithm based on Chaos Adaptive Hunger Games Search with Dynamic Lévy Mutation Strategy (CAHGSL) is proposed in this paper. By introducing an improved logistics chaos map initialization population, a nonlinear adaptive convergence factor and a dynamic Lévy mutation strategy enhance their ability to jump out of local extremes during multi-peak MPPT and improve their tracking speed and efficiency. Results: Under the three working conditions, the tracking efficiency of the MPPT algorithm proposed in this paper has been achieved by more than 99.5% in an average time of 0.152s, which is higher tracking efficiency compared to the PO, PSO, and HGS algorithms. Conclusion: The results show that the MPPT algorithm proposed in this paper can balance the tracking speed and efficiency with less power oscillation during the tracking process, and can ensure stable output after convergence. The method proposed in this paper is helpful to improve the output power of PV arrays under partial shading. © 2023 Bentham Science Publishers.

关键词： Efficiency

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YOLO-MSP: Effective Cigarette Detection YOLO Network for Surveillance Scenario 10

YOLO-MSP: Effective Cigarette Detection YOLO Network for Sur...

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10th International Conference on Systems and Informatics, ICSAI 2024

作者： Zhang, Zhiwei Lu, Xiaobo School of Automation Southeast University Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China

ISBN: (纸本)9798331510138

This paper presents an new approach to enhance the detection of smoking behavior using object detection neural networks, focusing on the challenge of small object detection, namely cigarettes in video frames. We introduce a Multi-Spatial Pooling (MSP) bottleneck mechanism integrated into a YOLOv8 backbone, which significantly improves the network's ability to discern smaller objects without compromising real-time inference capabilities. This enhancement facilitates the extraction of relevant features across various scales and efficiently handles the computational overhead, thereby boosting the detection accuracy and operational efficiency. Our results demonstrate a substantial improvement in performance metrics over traditional and existing neural network approaches, making this method highly suitable for real-time applications in diverse scenarios. © 2024 IEEE.

关键词： Deep learning

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MHDO-MAGE based Performance Optimization Strategy for Steam Generator Level control System ofNuclear Power Plant

MHDO-MAGE based Performance Optimization Strategy for Steam ...

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2024 China automation Congress, CAC 2024

作者： Shi, Jinguang Kong, Xiangsong Li, Xiaoyu Yang, Zean Chen, Weiming School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798350368604

The steam generator level control system is one of the critical control systems in a nuclear power plant, and its performance is vital for the safe and stable operation of the plant. The control parameters are key factors that affect the operational performance of the steam generator level control system. Therefore, during the commissioning of the nuclear power plant, it is usually necessary to adjust the parameters through the trial-and-error method. This tuning process mainly relies on the experience of the commissioning personnel and may potentially compromise plant safety due to human errors. Considering that the parameter tuning process of control systems can be regarded as a special type of batch processes, this paper proposes to apply an efficient data-driven optimization method, multi-source hybrid data-driven optimization method based on model accuracy gradient estimation (MHDO-MAGE), to the problem of parameter tuning for the steam generator control system. This method effectively combines the advantages of traditional MBO (Model-Based Optimization) and MFO (Model-Free Optimization) methods, while efficiently utilizing prior data information related to the optimization problem. This method was implemented on a widely adopted steam generator control system model specifically designed for steam generator simulations. The simulation results clearly indicate that the MHDO-MAGE method significantly enhances the efficiency of parameter tuning for the steam generator level control system, ultimately leading to a reduction in the costs associated with nuclear power plant commissioning. © 2024 IEEE.

关键词： Nuclear power plants

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PMSM System Identification by Knowledge-informed Machine Learning 22

PMSM System Identification by Knowledge-informed Machine Lea...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Yu, Yue Tong, Jiageng Xia, Jinhui Su, Jinya Li, Shihua School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9798331527471

Because of its excellent efficiency, compact dimensions, and accurate control features, Permanent Magnet Synchronous Motor (PMSM) are experiencing widespread applications across various industries. By accurately characterizing the dynamic behavior of PMSM systems through system identification, engineers can ensure that PMSM motors reach their maximum potentials and meet the stringent requirements of modern industrial and technical systems while reducing energy consumption and maintenance costs. The traditional recursive least squares method is sensitive to noises, and unable to accurately identify parameters in complex environments. Pure data-driven models lack interpretability and require complex model architecture and computational costs. To this end, this work draws knowledge-informed neural ordinary differential equations (NODEs) for system identification, which embeds system prior knowledge into the NODEs for more efficient and accurate model learning. Comparative simulations show that this method not only obtains a higher-precision system model, but also significantly reduces the amount of training data and computation costs. © 2024 IEEE.

关键词： Cost reduction

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Intelligent and Optimal System for Monitoring Environmental Variables and Solar Luminosity, with solar path tracker and telemetry

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2024年第5期22卷 43-48页

作者： Alan Calderón Ch, J. Gamarra, Benjamín Barriga Tafur Sotelo, Julio C. Ugarte, Fernando Jiménez Applied Nanophysics Institute for Physics Technical University of Ilmenau Ilmenau98693 Germany Control Engineering and Automation Master Program Mechatronic Engineering Master Program Energy laboratory Engineering Department Pontificia Universidad Católica del Perú Peru Aplicaciones Avanzadas en Sistema Mecatrónicos JACH S. A. C

In this proposed research are analyzed general solutions and techniques to optimize the solar luminosity measurement by a designed smart system, as well as its usability by the solar energy conversion and its storing. However, many times, this kind of systems have not an optimal solar path tracker and as a consequence it can not be measured the full solar luminosity during all the day, therefore, in this work are designed optimal mathematical models and algorithms to enhance the solar path tracker according to measure solar luminosity and getting optimal solar energy conversion/storing, which is useful to study geographical conditions before to build solar energy conversion centers. As well as, in this research also is studied and suggested some techniques to get wireless data communication regarding the measured environmental variables, measured solar luminosity and stored electrical energy as a consequence of the solar energy conversion, which can be transmitted, so far away, to a central monitoring center by Radio Frequency (RF) waves. © 2024, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： energy-saving Modulating Function (MF) nanostructures smart sensors Solar path tracker transducers wireless data transmission

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PWM Wave-Based Cooperative Vector control of Multiple Stepper Motors for Unmanned Surface Vehicles 7

PWM Wave-Based Cooperative Vector Control of Multiple Steppe...

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7th Asian Conference on Artificial Intelligence Technology, ACAIT 2023

作者： Xu, Ruizhe Xu, Yihang Wu, Yongbao Liu, Jian Xue, Lei Southeast University Key Laboratory of Measurement And Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing China

ISBN: (纸本)9798350359145

This paper studies the control system of multiple stepper motors. Four stepper motors are selected to design the vector control system for the actual application scenario of the unmanned surface vehicles. This paper designs a PWM wave-based motor control algorithm taking into account the characteristics of stepper motors. We proposes a closed-loop control algorithm incorporating magnetic encoders. The system applies CAN bus to realize the communication among stepper motors, enabling distributed cooperative control four stepper motors of the unmanned surface vehicles. In this paper, the multiple stepper motor system is modeled and finally simulated and experimentally verified to achieve cooperative vector control of multiple stepper motors for surface vehicles. © 2023 IEEE.

关键词： Vectors

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