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7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Meng, Defang Yu, Wei Shanghai University of Electric Power College of Automation Engineering Shanghai China HuaDian Electric Research Institute Department of Control Engineering Hangzhou China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

Aiming at the randomness and intermittent characteristics of renewable energy power generation, a capacity optimization method of a hybrid energy storage system is proposed to ensure the economical and reliable operation of wind and solar power supply systems. The optimization method takes the minimum life cycle cost of the hybrid energy storage system as the optimization goal, takes the load power shortage rate and the energy storage capacity as the constraints, and establishes the optimal configuration model of the hybrid energy storage capacity. Based on this model, the modified gray wolf algorithm (MGWO) is used to solve the optimal capacity configuration of the hybrid energy storage system. Finally, the optimization results of MGWO are compared with the basic GWO and particle swarm algorithm (GWO) through a numerical example, and it is verified that MGWO can configure the hybrid energy storage capacity more reasonably. © 2022 IEEE.

关键词： Wind power

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Thermal Cycling Effect in a Traction Inverter for Star-connected and Open-end Winding Permanent Magnet Synchronous Motors with Nearly Constant Losses Current Regulation 29

Thermal Cycling Effect in a Traction Inverter for Star-conne...

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29th International Workshop on Electric Drives: Advances in Power Electronics for Electric Drives, IWED 2022

作者： Ali, Yousef Kulik, Egor Anuchin, Alecksey Do, Duy Hiep Moscow Power Engineering Institute Department of Electric Drives Moscow Russia Thuyloi University Department of Automation and Control Engineering Hanoi Viet Nam

ISBN: (纸本)9781665467865

One of the causes of faults in the electric drive is the failure of the power semiconductor module. Semiconductors degrade under the effect of thermal cycles. Thermal aging of materials occurs due to temperature difference between the elements of the power module as well as difference of their thermal expansion coefficients, which eventually leads to the destruction of the power module construction. The influence of thermal cycles is most expressed in traction drives, which are characterized by modes with low speeds and variation of commanded torque in time. This article considers a BMW i3 electric drive model and an open-end winding drive with Nearly Constant Losses Current Regulation for evaluating thermal cycles in a power module. The new European driving cycle was used as a test cycle for both drives. It is shown how the proposed algorithm makes it possible to reduce the thermocycling effects in semiconductor devices. © 2022 IEEE.

关键词： Thermal cycling

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Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

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A Staged Model-Free Adaptive control for Infrared Heating System 5

A Staged Model-Free Adaptive Control for Infrared Heating Sy...

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5th International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2024

作者： Li, Xilong Luo, Yi Yang, Xiaojing Cheng, Taobo Xu, Zhihao School of Electrical and Mechanical Engineering Kunming University of Science and Technology Yunnan Kunming650500 China Institute of Intelligent Manufacturing Gdas Guangdong Key Laboratory of Modern Control Technology Guangzhou China School of Mechanical and Automation Engineering Wuyi University Jiangmen China

ISBN: (纸本)9798350385557

Due to the significant uncertainty and complexity present in the working process of the infrared heating system, as well as the system's strong nonlinear and time-varying characteristics, the traditional temperature control method does not perform well when dealing with such strong nonlinear and time-varying systems. Therefore, the model-free adaptive control algorithm is introduced into the control process of the infrared heating system. This paper first analyzes the heat transfer mechanism of the infrared heating system and establishes a mathematical model for it. Furthermore, to further enhance the control dynamic performance of the infrared heating system, a staged model-free adaptive control method is proposed. Initially, a proportional control term is added to the basic model-free control law, and subsequently, a variable coefficient 'b' is introduced into the original deviation-overcoming term. Finally, simulations are conducted using MATLAB to verify the effectiveness of the proposed control method. The simulation results indicate that the s-MFAC method offers better versatility and flexibility than the original MFAC method, significantly improving the system's overshoot and response speed. © 2024 IEEE.

关键词： MATLAB

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Non-cooperative Game-Oriented Optimal Prescribed Performance control for Underactuated Mechanical Systems with Asymmetric Constraints

Non-cooperative Game-Oriented Optimal Prescribed Performance...

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2024 China automation Congress, CAC 2024

作者： Liu, Lian Wei, Cui Chen, Ye-Hwa Zhang, Dengfeng Wei, Yanling College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta United States School of Automation Southeast University Nanjing China

ISBN: (纸本)9798350368604

This paper explores the application of non-cooperative game theory in achieving optimal prescribed performance control for uncertain underactuated mechanical systems. The study addresses scenarios characterized by time-varying (potentially rapid) and bounded uncertainties. Utilizing a constraint-following control design approach, we apply the prescribed transient and steady-state performance (TSSP) criteria to the constraint-following error. Additionally, we employ state transformation techniques to implement the prescribed performance control. We introduce a prescribed performance control methodology with two adjustable parameters and demonstrate the process of determining the optimal design for these parameters through Nash games. Our findings indicate a significant enhancement in the overall system performance, thus confirming the efficacy of the optimization method grounded in non-cooperative game theory. © 2024 IEEE.

关键词： Optimal control systems

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Reliability Allocation of Cruise Ship automation System Based on BBWM-AHP 6

Reliability Allocation of Cruise Ship Automation System Base...

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6th International Conference on System Reliability and Safety engineering, SRSE 2024

作者： Xiang, Jiaxin Sun, Yongquan Wang, Hao Chen, Hongke Harbin University of Science and Technology School of Measurement and Control Technology and Communication Engineering Harbin China China Institute of Marine Technology & Economy Beijing China Xiamen University Tan Kah Kee College School of Mechanical and Electrical Engineering & Automation Zhangzhou China

ISBN: (纸本)9798350356083

Limited reliability data during the development of cruise ship automation systems often leads to subjective weight allocation. This paper proposes an reliability allocation method based on the Bayesian best-worst method and analytic hierarchy process to address this challenge. By considering the system reliability indices, influencing factors, and units need to be allocated, a hierarchical model is established for reliability allocation based on the analytic hierarchy process. The Bayesian best-worst method compares elements in each layer, generating best and worst matrices based on decision-makers. These matrices determine optimal weights for each layer's elements. The analytic hierarchy process determines relative importance weights among the system reliability index, influencing factors, and units. Consequently, the derived optimal weights are converted into allocation factors, which enable the allocation of reliability for cruise ship automation systems. This fusion-based approach presents a novel and effective method for optimizing reliability allocation during the development stage of complex systems. © 2024 IEEE.

关键词： Decision making

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SMALL-SIGNAL STABILLITY ANALYSIS OF FLUX-controlLED GRID-FORMING DFIG UNDER WEAK GRID 20

SMALL-SIGNAL STABILLITY ANALYSIS OF FLUX-CONTROLLED GRID-FOR...

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20th International Conference on AC and DC Power Transmission 2024, ACDC 2024

作者： Wang, Wenhe Hu, Yufei Li, Weibing Hua, Xiaojun Zha, Xiaoming Tian, Zhen School of Electrical Engineering and Automation Wuhan University Wuhan China Laboratory of Hydro-Wind-Solar Multi-energy Control Coordination Wuhan China Institute of Science and Technology China Three Gorges Corporation Beijing China

ISBN: (纸本)9781837242672

With the continuous increase of global wind power installed capacity, the modern power system gradually shows the characteristics of weak damping, low inertia, and weak anti-interference ability. Aiming at the normal grid-connected wind tur-bine under weak grid conditions, the small signal stability of the flux-controlled grid-forming DFIG is analysed. Firstly, the small-signal model of the flux-controlled grid-forming DFIG is constructed based on the flux-controlled virtual synchronous generator control (VSG). Then, the eigenvalue analysis method is used to investigate the influence of different operating conditions and controller parameters on the small-signal stabilization of system. Besides, the dominant factors of low-frequency oscillatory modes are analysed based on the participation factor matrix. Finally, the safety and stability boundaries of each influencing factor are calculated by oscillation modal analysis, which provides guidance for the parameter design of the DFIG underweak grid. © The Institution of engineering & Technology 2024.

关键词： Eigenvalues and eigenfunctions

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Asynchronous State Estimator Design for Markov Switched Systems with Incomplete Probabilities and Redundant Channels 42

Asynchronous State Estimator Design for Markov Switched Syst...

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42nd Chinese control Conference, CCC 2023

作者： Chen, Haiyang Gao, Fangzheng Mao, Xueyi School of Control Science and Engineering Tiangong University Tianjin300387 China School of Automation Nanjing Institute of Technology Nanjing211167 China Nanjing Communications Institute of Technology Publicity Department Nanjing211188 China

ISBN: (纸本)9789887581543

This paper is concerned about the H∞ asynchronous state estimator design for Markov switched systems (MSSs) with incomplete transition probabilities and redundant channels. A hidden Markov chain (HMC) is introduced to characterize the asynchronous degree between the state estimator mode and the system mode. Firstly an asynchronous full-order state estimator is devised for the MSSs. Then, by Lyapunov functional and stochastic analysis, new criteria are derived such that the augmented system consisting of the target system and state estimator is H∞ stochastically finite-time boundedness. After that, with matrix decoupling technique, a design algorithm is obtained in form of linear matrix inequalities (LMIs). Finally, the practical one-link robotic manipulator is utilized to validate the developed results. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Linear matrix inequalities

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Short-term Power Load Prediction based on Temporal Feature Clustering

Short-term Power Load Prediction based on Temporal Feature C...

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2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2023

作者： Wang, Xu Jin, Jianxun Wang, Heyang Liaoning Technical University School of Electrical and Control Engineering Liaoning Huludao China Tianjin University School of Electrical Automation and Information Engineering Tianjin China University of Chinese Academy of Sciences Institute of Electrical Engineering Cas Beijing China

ISBN: (纸本)9798350301571

This study categorizes the predicted load sequences into two types, namely 'normal short cycle' and 'characteristic short cycle', and analyzes their respective characteristics. Subsequently, a 'feature prediction' model is developed using the genetic optimization BPNN algorithm, while a 'general prediction' model is constructed using the GLSTM algorithm. The performance of these models is compared with other methods, and the findings demonstrate that the deviation of the model proposed in this paper is only 2.86%. This result validates the accuracy and feasibility of the proposed method. © 2023 IEEE.

关键词： Electricity load forecasting LSTM portfolio optimization time-series characterization

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Time-Constrained Cooperative Guidance Based on Deep Neural Network 42

Time-Constrained Cooperative Guidance Based on Deep Neural N...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Changhai Yu, Jianglong Dong, Xiwang Li, Qingdong Ren, Zhang Wang, Feifei Hu, Xijing School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Institute of Control and Electronic Technology Beijing100038 China

ISBN: (纸本)9789887581543

Time-constrained cooperative guidance based on deep neural network (DNN) is developed to address the problem of cooperative guidance of multiple missiles against maneuvering targets. Firstly, deep neural network is applied to estimate time-to-go. A simplified dataset is created to improve the estimation effect and the performance of training results is good. Secondly, time-constrained cooperative guidance law is designed. Time-constrained guidance (TCG) law based on variable navigation ratio is proposed and an optimal method of cooperative time is designed. Thirdly, simulation in 3-D space and equivalent experiment in 2-D space are carried out to verify the performance of guidance law. An equivalent experiment platform based on multiple unmanned ground vehicles (Multi-UGVs) is erected and the experiment to achieve cooperative guidance is carried out. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Deep neural networks

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