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European control Conference (ECC)

作者： Manuel Lara Francisco Vázquez Jan-Willem van Wingerden Sebastiaan Paul Mulders Juan Garrido Department of Electrical Engineering and Automation University of Cordoba Cordoba Spain Delft Center for Systems and Control Faculty of Mechanical Engineering Delft University of Technology Delft The Netherlands

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In order to mitigate periodic blade loads in wind turbines, recent research has analyzed different Individual Pitch control (IPC) approaches, which typically use the multi-blade coordinate (MBC) transformation. Some of these studies show that the introduction of an additional tuning parameter in the MBC, namely the azimuth offset, helps to decouple the nonrotating axes in the MBC transformation and enhances the IPC performance. However, these improvements have been studied without considering the increased control effort performed by the pitch signal, which is the main negative side effect of the IPC. This work addresses this trade-off between pitch signal effort and blade fatigue reduction for IPC applied to a wind turbine operating in the full load region. Here, two IPC schemes, with and without additional azimuth offset, are designed and applied to a 15 MW monopile offshore wind turbine simulated with OpenFAST software. The optimal tuning of the IPC parameters is performed by means of a multi-objective optimization solved by genetic algorithms. The optimization procedure minimizes two objective functions related to pitch signal effort and blade fatigue load. The resulting Pareto fronts show a range of optimal solutions for each IPC scheme. The selected optimal solution for IPC with azimuth offset compared to the optimal solution for IPC without offset achieves improvements of more than 10% in blade load reduction maintaining similar pitch signal effort.

关键词： Azimuth Blades Simulation Fatigue Linear programming Software Wind turbines

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Securing the Future after Pager Bombs:Lifecycle Protection of Smart Devices via Blockchain Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2355-2358页

作者： Fei Lin Qinghua Ni Jing Yang Juanjuan Li Nan Zheng Levente Kovács Radu Prodan Mariagrazia Dotoli Qing-Long Han Fei-Yue Wang the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBei-jing 100049China IEEE Obuda University John von Neumann Faculty of InformaticsBecsi Str.96/bH-1034 BudapestHungary the Institute of Information Technology University of Klagenfurt9020 Klagenfurt am WortherseeAustria the Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190

THE Lebanese wireless device explosion incident has drawn widespread attention,involving devices such as pagers,walkie-talkies,and other common devices[1].This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment,signaling the onset of a new wave of"supply chain warfare"[2].

关键词： Smart cycle chains

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Closed loop systems

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A Dynamic Event-Triggered Transmission Strategy for Distributed Convex Optimization 42

A Dynamic Event-Triggered Transmission Strategy for Distribu...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Pengfei Liu, Kun-Zhi Zhang, Dianfeng Du, Shengli Dalian University of Technology Academy of Control Science and Engineering Dalian116024 China School of Mathematics and Informational Science Yantai University Yantai100124 China College of Automation Faculty of Information Technology Beijing University of Technology Yantai100124 China

ISBN: (纸本)9789887581543

A dynamic event-triggered transmission strategy is considered for the continuous-time distributed convex optimization algorithm over a strongly connected and weight-balanced directed graph. An auxiliary variable is introduced in the dynamic event-triggered control (DETC) that is free of Zeno phenomenon. We model the DETC system into a hybrid system. Using Lyapunov stability theory, we give a detailed proof for convergence of the continuous-time distributed convex optimization algorithm. Finally, a numerical simulation shows that the DETC can effectively save network communication resources compared with a static event-triggered control (SETC). © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Convex optimization

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A Dual-Channel Nonlinear Method for Crude Copper Grade Prediction Based on LSTM-Attention and GWO-RF

A Dual-Channel Nonlinear Method for Crude Copper Grade Predi...

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第43届中国控制会议

作者： Qinghang Guan Chunxi Yang Xiufeng Zhang Jin Zhang Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Yunnan International Joint Laboratory of Inteligent Control and Application of Advanced Equipment Faculty of Information Engineering and Automation Kunming University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Converter blowing is the key process method for refined copper extraction, characterized as a large-hysteresis, weakly robust, nonlinear system. The grade of crude copper directly impacts the quality and technological level of refined copper,making it essential to establish a predictive model for crude copper grade. In this paper, a new two-channel nonlinear method LAGR-ELM is proposed. Initially, wavelet denoising method is used to improve the data quality. Subsequently, the first channel is based on LSTM combined with Attention mechanism to predict the crude copper grade by using its ability to capture the hidden temporal information of the data, and the second channel employs the Grey Wolf Optimizer to optimize the Random Forest algorithm. Then, a nonlinear aggregation mechanism based on ELM is used to address the inherent shortcomings of single methods and linear combinations. The effectiveness is validated using real data from a copper smelting plant in *** comparing with eight prediction methods, the simulation results show that LAGR-ELM can achieve better prediction results.

关键词： Wavelet denoising LSTM Random forests Extreme learning machines Nonlinear combination Two-channel prediction Crude copper grade prediction

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From DAO to TAO: Finding the Essence of Decentralization

From DAO to TAO: Finding the Essence of Decentralization

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Li, Juanjuan Liang, Xiaolong Qin, Rui Wang, Fei-Yue Institute of Automation State Key Laboratory of Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Macau999078 China Institute of Automation State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9798350337020

Decentralized Autonomous Organizations (DAOs) have been gaining popularity in recent years due to their promise of realizing the decentralized Web 3.0. However, most DAOs rely heavily on token-centric value systems as well as allocate decision-making authority and yield-sharing rights according to the held tokens, which often lead to monopolization of power and rights. To address this issue, this paper contributes to propose a truly democratic organization model, named True Autonomous Organizations and Operations (TAOs), that does not count upon tokens and is guided by principles of contribution-based and on-demand allocation. We first discuss the design of TAOs, including their infrastructures, power structures, and value systems, and then provide a technical roadmap for implementing TAOs in the DeSci context. This research can provide a valuable guidance for the construction and application of TAOs. © 2023 IEEE.

关键词： Decentralized Autonomous Organizations and Operations (DAOs) governance systems open consortium blockchain True Autonomous Organizations and Operations (TAOs) value systems

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Management-Oriented Operating Systems: Harnessing the Power of DAOs and Foundation Models

Management-Oriented Operating Systems: Harnessing the Power ...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Qin, Rui Li, Juanjuan Liang, Xiaolong Wang, Fei-Yue Institute of Automation State Key Laboratory of Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Macau999078 China Institute of Automation The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9798350337020

This paper presents Management-Oriented Operating Systems (M2OS) that leverages the power of parallel intelligence theory, Decentralized Autonomous Organizations (DAOs) and foundation models to revolutionize the manner of management in Cyber-Physical-Social Systems (CPSS). The parallel architecture on M2OS is proposed, including the parallel interactive actual M2OS and artificial M2OS. Among them, the artificial M2OSs provide digital infrastructures for organizations to operate, collaborate, and make decisions in the virtual space, and conduct computational experiments to evaluate management decisions and predict future states of the actual M2OS. Through parallel execution and closed-loop feedback between the artificial and actual M2OSs, the management and control, experimentation and evaluation, as well as learning and training of the actual M2OS can be realized. Moreover, the functional layers of M2OS, including the infrastructure layer, data layer, scenario layer, modeling layer, decision layer, and application layer, are discussed. These layers work together to support the intelligent, autonomous, collaborative, and adaptive nature of the M2OS, and facilitate data-driven decision-making, optimize business operations, and empower managers with real-time actionable insights. The proposed M2OS paradigm has great potential to transform the management paradigm and opens up new possibilities for intelligent and collaborative decision-making. © 2023 IEEE.

关键词： cyber-physical-social systems Decentralized Autonomous Organizations foundation models management-oriented operating systems parallel intelligence

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Robust controller Design with Two-Degree-of-Freedom Feedback Loop Factorization for Oscillating Plant with Uncertain Time Delay*

Robust Controller Design with Two-Degree-of-Freedom Feedback...

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International Conference on control, automation and Diagnosis (ICCAD)

作者： Marek Dlapa Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Zlin Czech Republic

Application of Robust control Toolbox for Time Delay Systems implemented in the Matlab system to the oscillating plant with uncertain time delay using the D-K iteration and algebraic approach. The algebraic approach combines the structured singular value, algebraic theory and algorithm of global optimization solving remaining issues in structured singular value framework. The algorithm of global optimization can be alternated with direct search methods such as Nelder-Mead simplex method giving solutions for problems with one local extreme. As a global optimization method, Differential Migration is used proved to be reliable in solving this type of problems. The D-K iteration represents a standard method in the structured singular value theory. The results obtained from the D-K iteration are compared with the algebraic approach.

关键词：

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Object Recognition and Grasp Detection in Complex Scenarios for Home Service Robot

Object Recognition and Grasp Detection in Complex Scenarios ...

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Chinese automation Congress (CAC)

作者： Shengjun Xu Liang Bai Huangwei Zhong Yuji Hu Xiangcai Sun Hongqiang Lyu School of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China School of Automation Science and Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

With the development of artificial intelligence, home service robots have been widely applied in daily life. As one of the fundamental functions of service robots, object grasping helps improve the level of unmanned and intelligent household. However, traditional robots still face challenges in flexibility and accuracy in complex home environments. In this paper, an object recognition and grasp detection system in complex scenarios for home service robots is proposed. The system consists of four modules: image acquisition, human-machine interaction software, RGB-D image processing, and robot control. The image acquisition module captures RGB and depth images of the work area and sends them to the software. The RGB-D image processing module begins with object recognition to obtain object categories and bounding box with the help of YOLOv8. The target point cloud is produced by combining the target subimage and corresponding depth information, followed by depth completion and plane expansion. Then the processed point cloud is fed into a Graspnet pose estimation network to calculate the 6D grasping pose for service robot. And finally, the robot control module is invoked to carry out the corresponding target grasping action. To evaluate the performance, an experimental platform for home service robot is built to grasp various daily necessities. The results tell that the average accuracy for object recognition reaches up to 98.3%, the success rate for single-target grasping is 94.4%, and the success rate for multi-target grasping can achieve 80%.

关键词： Point cloud compression Human computer interaction Visualization Service robots Image processing Robot control Pose estimation Grasping Software Object recognition

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State of Health Assessment of Lithium Batteries Based on Fusion Model and Feature Extraction

State of Health Assessment of Lithium Batteries Based on Fus...

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Cognitive Computing and Complex Data (ICCD), International Conference on the

作者： Qiwei Zhang Yulong Li Peipei Cai Rongkai Zhao Tian Peng Smart Energy Division Huadong Engineering Corporation Limited Hangzhou China Automation Engineering Room Hangzhou Huachen Power Control Engineering Corporation Limited Hangzhou China Beidou Innovation Studio Hangzhou Huachen Power Control Engineering Corporation Limited Hangzhou China Faculty of Automation Huaiyin Institute of Technology Huai’an China

ISBN: (数字)9798350352894

ISBN: (纸本)9798350352900

Lithium battery State of Health (SOH) is crucial for stable operation and reducing failure risks. This paper identifies three key health features—IC curve peak value, constant voltage drop discharge time, and IC curve peak voltage—through Pearson correlation analysis. A multi-model fusion approach is utilized to construct and train three individual models: Temporal Convolutional Network (TCN), Extreme Learning Machine (ELM), and Long Short-Term Memory Network (LSTM). Additionally, three pairwise fusion models—TCN-LSTM, TCN-ELM, and ELM-LSTM—and a comprehensive TCN-LSTM-ELM model are developed. Validation using NASA dataset shows that TCN-LSTM-ELM fusion model achieves the highest prediction accuracy.

关键词： Training Accuracy Computational modeling Voltage Predictive models Lithium batteries Data models Integrated circuit modeling Optimization Long short term memory

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