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26th International Conference on electrical Machines and Systems, ICEMS 2023

作者： Yang, Ming Wang, Qunjing Zhou, Rui Li, Guoli Wen, Yan Anhui University School of Electrical Engineering and Automation Hefei China Quality Control Anhui University Collaborative Innovation Center of Industrial Energy-Saving and Power Hefei China Anhui University National Engineering Laboratory of Energy-Saving Motor and Control Technology Hefei China Anhui University School of Internet Hefei China

ISBN: (纸本)9798350317589

In order to analyze and optimize the structure of existing permanent magnet spherical motors, a method for 3D motion singularity analysis of permanent magnet spherical motors is presented in this paper. This calculation model of the motion singularity is established on the basis of the spherical motor's torque model by judging that the torque value is too small. Using this model to calculate the distribution of motion singularities, we can judge whether the structure of the spherical motor is reasonable or not. For this model, a singularity representation method is presented to visually represent the specific distribution of singularities. This method can be used to compare different optimization schemes, and select the optimal structure with better motion performance. © 2023 IEEE.

关键词： Structural optimization

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Design of an aircraft autonomous traction taxiing system based on hydraulic secondary control

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Chinese Journal of Aeronautics 2024年第6期37卷 348-359页

作者： Xiaochao LIU Zhongyi QIU Hao ZHANG Pengyuan QI Zhenyu WANG Yaoxing SHANG Zongxia JIAO Research Institute for Frontier Science Beihang UniversityBeijing 100083China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China Ningbo Institute of Technology Beihang UniversityNingbo 315800China Tianmushan Laboratory Xixi Octagon CityYuhang DistrictHangzhou 310023China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100083China Beijing Tianma Intelligent Control Technology Co. Ltd.Beijing 101399China China Coal Research Institute Beijing 100013China

At present,aircraft taxiing at ground airports needs to be provided with a thrust by the main *** taxiing process is inefficient,has high fuel consumption and serious pollution,and is prone to safety *** this paper,a new configuration of aircraft autonomous traction taxiing system is proposed based on the principle of hydraulic secondary control,in which a hydraulic motor drive device is installed at the front wheels of the aircraft to drive the wheels to rotate forward or *** on this,autonomous taxiing can be realized without relying on the main engines,thus greatly improving airport operation ***,this paper analyzes the influencing factors of the autonomous traction taxiing process,and investigates the parameter matching design of the new configuration ***,this paper develops the ground principle prototype,designs the aircraft longitudinal bonding force observer and the aircraft wheel disturbance moment observer,and proposes the speed control method of the aircraft front wheel autonomous traction taxiing by considering the ground bonding force saturation ***,the ground taxiing test is conducted,and the results show that the new configuration proposed in this paper presents a new solution for aircraft autonomous traction taxiing.

关键词： Autonomous traction taxi-ing Hydraulic secondary control Hydraulic motors Saturation characteristics Disturbance observation Speed control

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Establishment of Degradation Model and Transfer Model for P-channel Power MOSFETs Under Negative Bias Temperature Stress

Establishment of Degradation Model and Transfer Model for P-...

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International Conference on Power Electronics and Motion control (IPEMC)

作者： Cen Chen Haodong Wang Haonan Yin Wei Zheng Guofu Zhai School of Electrical Engineering and Automation Harbin Institute of Technology China Beijing Aerospace Automatic Control Institute China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

Negative Bias Temperature Instability (NBTI) is the main reason for the degradation of gate oxide in P-channel power MOSFETs. Affected by long-term negative bias gate voltage and high temperature, the threshold voltage of power MOSFETs drifts, which in turn affects the performance of the device. Based on the analysis of NBTI failure mechanism, this paper conducted accelerated degradation test on six different types of P-channel power MOSFETs. Secondly, the Iterative Reweighted Least Square (IRLS) method was applied to establish a threshold voltage drift’s degradation model, which can accurately describe actual degradation data. In addition, a transfer model was established using multiple linear regression theory to approximately describe the relationship between the fitting parameters of degradation model and power MOSFETs’ process parameters, providing a new approach for the fast reliability assessment of P-channel power MOSFETs.

关键词： Semiconductor device modeling Degradation Negative bias temperature instability MOSFET Thermal variables control Fitting Life estimation

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PITD3-based Autonomous Evasion Decision-making Method for Aircraft

PITD3-based Autonomous Evasion Decision-making Method for Ai...

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第43届中国控制会议

作者： Chang Liu Liqian Dou Ruilong Zhang Yifan Tang Mengyuan Ren Lun Zhang School of Electrical Engineering and Automation Beijing Aerospace Automatic Control Institute Tianjin Aerospace Institute of Computing Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Outstanding autonomous evasion decision-making capability has an important significance for ensuring flight safety and enhancing the autonomy of the aircraft. In this paper, a prediction information-based TD3(PITD3) evasion decision-making algorithm for aircraft is proposed, which can autonomously evade the interceptors' attack in an antagonistic environment. Firstly,an antagonistic environment is described according to environmental constraints and the dynamics of the aircraft and interceptor. Secondly, the autonomous decision-making process of the aircraft facing the threat target is modelled as a Markov decision process to describe the state information of the aircraft and interceptor. Finally, an autonomous evasion decision-making method based on the twin delayed deep deterministic policy gradient(TD3) is designed to find the optimal strategy, and the effectiveness of the proposed autonomous evasion decision-making method is demonstrated by simulation results and comparative experiments.

关键词： PITD3 Autonomous Evasion Decision-Making Deep Reinforcement Learning Decision Network Aircraft

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A data-driven disturbance estimation algorithm based on adaptive observer for MIMO linear systems

A data-driven disturbance estimation algorithm based on adap...

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第34届中国过程控制会议

作者： Xiaoyi Xu Hao Luo Xiao Zhang Department of Control Science and Engineering Harbin Institute of Technology Department of Automation Science and Electrical Engineering Beihang University

The adaptive observer is a well-developed datadriven algorithm for co-estimation of system parameters and ***,inevitable disturbances can affect the systems and lead to deterioration of the algorithm *** disturbance estimation methods require prior knowledge about model parameters and disturbance *** paper presents a robust adaptive observer method for multiple-inputmultiple-output linear systems subject to *** proposed method can perform joint estimation of unknown parameters,states and disturbances without any prior information about the model parameters and *** stability and convergence of the algorithm are rigorously proved to ensure that the estimation errors converge exponentially to *** results of a numerical example demonstrate the effectiveness of the algorithm.

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Reinforcement Fuzzy Q-Learning Incorporated with Genetic Kinematics Analysis for Self-organizing Holonomic Motion control of Six-Link Stewart Platforms

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International Journal of Fuzzy Systems 2023年第3期25卷 1239-1255页

作者： Huang, Hsu-Chih Xu, Sendren Sheng-Dong Chen, Yu-Xiang Chen, Chien-Ming Department of Electrical Engineering National Ilan University Yilan260007 Taiwan Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taipei106335 Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taipei106335 Taiwan

This paper contributes to the development of reinforcement fuzzy Q-learning incorporated with genetic kinematics analysis for self-organizing holonomic motion control of six-link Stewart platforms. The fuzzy theory is integrated with the Q-learning algorithm to develop a hybrid reinforcement learning strategy. Both the actions and the Q-functions in the classical Q-learning algorithm are inferred by means of fuzzy rules. The proposed hybrid reinforcement learning is then applied to self-organizing holonomic motion control of parallel Stewart platforms for industrial applications. After the kinematics analysis using a geometrical approach and genetic algorithm (GA)-based Newton–Raphson formulation, this study develops a practical control scheme that combines fuzzy Q-learning and proportional–integral–differential (PID) control scheme, called FQPID. In the proposed FQPID holonomic motion control method, the PID control gains are online-tuned via the fuzzy Q-learning computation process. An experimental Stewart platform consisting of six servo motors, adjustable links, and two platforms is constructed to illustrate the effectiveness of the presented methods. The experimental results are compared with some existing control methods using the same evaluation criterion. Through the experimental results and comparative works, the superiority of the proposed FQPID control scheme is presented and discussed. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.

关键词： Reinforcement learning

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Subspace Identification of a MIMO Wafer Rapid Thermal Processing System

Subspace Identification of a MIMO Wafer Rapid Thermal Proces...

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2022 Chinese automation Congress, CAC 2022

作者： Liu, Xiao-You Bian, Yan Geng, Li-Hui Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin300222 China

ISBN: (纸本)9781665465335

This paper studies the subspace identification of a MIMO wafer rapid thermal processing (RTP) system driven by standard tungsten halogen lamps and output temperatures for the RTP system are measured by pyrometers. In order to estimate a linearized dynamic model for the nonlinear RTP system at an environmental temperature, input voltages for the lamps are selected as mutually independent pseudo-random binary series (PRBS). To design such PRBS to persistently excite the system, several pre-experiments for determining its settling time and maximum frequency are needed to be designed beforehand. Finally, the effectiveness of the identification method is verified by a numerical simulation. © 2022 IEEE.

关键词： Numerical methods

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Reactive Power Optimization of Active Distribution Network Based on Multi-objective Immune-simplex Method

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Dianwang Jishu/Power System Technology 2023年 47卷 35-39页

作者： Lin, Ying Huang, Wenying College of Electrical Engineering and Automation Fuzhou University Fujian Province Fuzhou350108 China College of Computer and Control Engineering Minjiang University Fujian Province Fuzhou350108 China

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System identification with binary-valued observations under both denial-of-service attacks and data tampering attacks:the optimality of attack strategy

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control Theory and Technology 2022年第1期20卷 127-138页

作者： Jin Guo Xuebin Wang Yanling Zhang Wenchao Xue Yanlong Zhao School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of EducationBeijing100083China Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China

With the development of wireless communication technology,cyber physical systems are applied in various fields such as industrial production and infrastructure,where lots of information exchange brings cyber security threats to the *** the perspective of system identification with binary-valued observations,we study the optimal attack problem when the system is subject to both denial of service attacks and data tampering *** packet loss rate and the data tampering rate caused by the attack is given,and the estimation error is *** the optimal attack strategy to maximize the identification error with the least energy is described as a min–max optimization problem with *** explicit expression of the optimal attack strategy is *** examples are presented to verify the effectiveness of the main conclusions.

关键词： System identification Binary-valued observations Denial-of-service attacks Data tampering attacks

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Fatigue Driving Vigilance Detection Using Convolutional Neural Networks and Scalp EEG Signals 2022

Fatigue Driving Vigilance Detection Using Convolutional Neur...

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7th International Conference on Multimedia and Image Processing, ICMIP 2022

作者： Fang, Yue Han, Chunxiao Liu, Jing Guo, Fengjuan Qin, Yingmei Che, Yanqiu Tianjin Key Laboratory of Information Sensing Intelligent Control School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781450387408

Fatigue driving is one of the important factors that cause traffic accidents. To solve this problem, this paper proposes a classification model based on the traditional convolutional neural network (CNN) to distinguish the vigilance state. First, the raw electroencephalogram (EEG) signals were converted into two-dimensional spectrograms by the short-Time Fourier transform (STFT). Then, the CNN model was used for automatic features extraction and classification from these spectrograms. Finally, the performance of the trained CNN model was evaluated. The average of area under ROC Curve (AUC) was 1, the sensitivity was 91.4%, the average false prediction rate (FPR) was 0.02/h, and the accuracy rate was as high as 97%. The effectiveness of the CNN model was verified by the evaluation results. © 2022 ACM.

关键词： Convolutional neural networks

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