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24th International Vacuum Electronics Conference, IVEC 2023

作者： Ma, Yuan Liu, Guo Cao, Yingjian Wang, Weijie Wang, Yu Jiang, Wei Yao, Yelei J., Wang Y., Luo University of Electronic Science and Technology of China Chengdu610054 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089 China

ISBN: (纸本)9781665473217

In this paper, the design and measurement of a mode-suppression circuit (MSC) applied in the nonlinear interaction region of a Ka-band gyrotron travelling wave tube (gyro-TWT) are presented. The proposed MSC is capable to suppress the spurious TE11 mode with no influence on the operating TE01 mode which helps to improve the tube stability for the high-power operation. Simulation result shows MSC can provide a loss of more than -5 dB around 23.1 GHz for the spurious TE11 mode which agrees well with the measured results. © 2023 IEEE.

关键词： Timing circuits

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Attitude Feedforward Compensation control for Multistage Satellite with Scanning Mechanism

Attitude Feedforward Compensation Control for Multistage Sat...

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2022 Chinese Automation Congress, CAC 2022

作者： Fan, Mao Tang, Liang Guan, Xin Guo, Zixi Hao, Renjian Zhang, Kebei Beijing Institute of Control Engineering Key Laboratory of Science and Technology on Space Intelligent Control Beijing China

ISBN: (纸本)9781665465335

In this paper, a multi-step prediction feed-forward compensation attitude control method based on the conservation of angular momentum is designed for multistage satellite with a two-dimensional scanning mechanism. Firstly, the dynamic model of multistage satellite with a scanning mechanism is established by the Newton-Euler method. Secondly, a multi-step prediction feedforward compensation method based on the conservation of angular momentum is proposed for the discrete multistage control system to solve the control period mismatching and the measurement delay. Finally, the numerical simulation shows that the control method proposed in this paper improves the attitude stability and pointing accuracy of multistage satellite by 3-4 times. © 2022 IEEE.

关键词： Attitude control

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Design and Cold Test of a Mode-Suppression Circuit for the G-Band Gyro-TWT 24

Design and Cold Test of a Mode-Suppression Circuit for the G...

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Cao, Yingjian Liu, Guo Ma, Yuan Wang, Yu Wang, Weijie Jiang, Wei Yau, Yelei Wang, Jianxun Luo, Yong University of Electronic Science and Technology of China Chengdu610054 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089 China

ISBN: (纸本)9781665473217

In this paper, the design and measurement of a mode-suppression circuit used in the nonlinear interaction region for a G-band gyrotron travelling wave tube (gyro-TWT) are presented. By achieving sufficient coupling losses, this circuit can effectively suppress the parasitic oscillations without affecting the operating mode, thus improving the tube stability during high power operation. The measured results agree well with the simulated results, which can provide a loss of 5.6 dB/cm to suppress the backward-wave oscillation (BWO) of the TE21 mode. This proves that the circuit can be used as a new scheme for gyro- TWTs to achieve high stability and high power. © 2023 IEEE.

关键词： Timing circuits

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State Feedback control of Distributed radar system with Packet dropouts and Time-varying delays 24

State Feedback Control of Distributed radar system with Pack...

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24th International Vacuum Electronics Conference, IVEC 2023

作者： Li, Xiaoxue Zhang, Yunjiao Yang, Jing Li, Qiaoyu Chen, Xu School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

ISBN: (纸本)9781665473217

In this paper, we present state feedback control for the distributed radar with packet dropouts and time-varying delays. The delays are time-varying. The packet dropouts mean the loss of the state measurement data. Firstly, the state feedback control design is transformed into stability analysis for a 2D stochastic system. Secondly, we obtain the stability condition based on linear matrix inequality (LMI) of mean-square asymptotic stability of the 2D stochastic system. And we give the method to get the law for the state feedback control design. The proposed method can stabilize the distributed radar with packet dropouts and time-varying delays. Finally, a numerical example is to show the validity of the methods. © 2023 IEEE.

关键词： Stochastic systems

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A Novel Grades Prediction Method for Undergraduate Students by Learning Explicit Conditional Distribution

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4837-4848页

作者： Zhang, Na Liu, Ming Wang, Lin Liu, Shuangrong Sun, Runyuan Yang, Bo Zhu, Shenghui Li, Chengdong Yang, Cheng Cheng, Yuhu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Shandong Key Laboratory of Intelligent Buildings Technology Jinan250101 China University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China Quan Cheng Laboratory Jinan250100 China Shandong Jianzhu University Shandong Key Laboratory of Intelligent Buildings Technology Jinan250101 China Shandong Jianzhu University School of Information and Electrical Engineering Jinan250101 China Ministry of Education Engineering Research Center of Intelligent Control for Underground Space Xuzhou221116 China

Educational data mining (EDM) offers an effective solution to predict students' course grades in the next term. Conventional grade prediction methods can be viewed as regressing an expectation of the probability distribution of the student's grade, typically called single-value grade prediction. The reliable prediction outcomes of these methods depend on the complete input information related to students. However, next-term grade prediction often encounters the challenge of incomplete input information due to the inaccessibility of future data and the privacy of data. In this scenario, single-value grade prediction struggles to assess students' academic status, as it may not be represented and assessed by relying on a singular expectation value. This limitation increases the risk of misjudgment, and may lead to errors in educational decision-making. Considering the challenge of collecting complete input information, we shift from traditional single-value predictions to forecasting the explicit probability distribution of the course grade. The probability distribution of the grade can assess the students' academic status by providing probabilities corresponding to all possible grade values rather than relying solely on an expectation value, which offers the foundation to support the educators' decision-making. In this article, the course grade distribution prediction (CGDP) model is proposed, aiming to estimate an explicit conditional probability distribution of course grades in the next term. This model can identify at-risk students, offering comprehensive decision-making information for educators and students. To ensure precise distribution predictions, a calibration method is also employed to improve the alignment between predicted and actual probabilities. Experimental results verify the effectiveness of the proposed model in early grade warning for undergraduates, based on real university data. © 2020 IEEE.

关键词： Probability distributions

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Imbalanced Fault Diagnosis of Key Components in spacecraft ACS via Collaborative ResNet

Imbalanced Fault Diagnosis of Key Components in Spacecraft A...

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2023 China Automation Congress, CAC 2023

作者： Ma, Shujun Mao, Zehui Liang, Hanyu Li, Shuyu College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Laboratory of Science and Technology on Space Intelligent Control Beijing China

ISBN: (纸本)9798350303759

In this paper, a fault diagnosis method based on Collaborative Residual Network (Collaborative ResNet) is proposed to address the problem of imbalanced fault diagnosis for key components of spacecraft attitude control system (ACS). The designed Collaborative ResNet consists of two branches, the conventional learning branch and rebalancing learning branch, which conduct representation learning and classifier learning, respectively. A new Dynamic Complementary Loss (DC Loss) is introduced in the rebalancing learning to dynamically alleviate the excessive gradient of negative samples on the few sample classes and compensate for the gradient of misdiagnosed samples, which enhances the network sensitivity to the class with few number samples. Then the features extracted by two branches are adaptively integrated through the collaborative learning strategy to combine the strengths of both approaches. The effectiveness of the proposed method was validated on the imbalanced data collected on a ground semi-physical platform. © 2023 IEEE.

关键词： Failure analysis

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A 7DOF redundant manipulator inverse kinematic solution algorithm based on bald eagle search optimization algorithm

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Soft Computing 2024年第23期28卷 13681-13699页

作者： Zhao, Guojun Sun, Ying Jiang, Du Liu, Xin Tao, Bo Jiang, Guozhang Kong, Jianyi Yun, Juntong Liu, Ying Li, Gongfa Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education 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 Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China

Solving inverse kinematics (IK) is an excellent challenge for redundant manipulators due to their highly non-linear and complex coupling, which is not amenable to analytical solutions by conventional methods. In this paper, the conventional solution was replaced by the optimization process of a fitness function. The fitness function aims to obtain a set of solutions for the desired position of the end effector (EE). The function is based on forward kinematics;hence, this method can avoid singularities and be suitable for solving redundant manipulators. For solving this optimization problem, the bald eagle search (BES) optimization algorithm was chosen due to its easy principle and excellent performance. BES integrates the advantages of evolutionary and swarm techniques. On the one hand, BES maximizes the advantages offered by swarm intelligence (SI) in terms of searching within the best position in the swarm. On the other hand, BES capitalizes on the capability of evolutionary techniques to explore the search space frequently and avoid the local optimum. In this study, two 7-degree of freedom (DOF) manipulators were used to test the performance of BES. Meanwhile, several evolutionary and SI optimization algorithms were selected to compare with BES. The experimental results demonstrate that the BES optimization algorithm can efficiently and accurately solve the IK problem of 7DOF redundant manipulators. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Inverse kinematics

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RUL Prediction of Turbofan Engine Based on WGAN-Trans under Small Samples

RUL Prediction of Turbofan Engine Based on WGAN-Trans under ...

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2023 China Automation Congress, CAC 2023

作者： Qi, Chenman Mao, Zehui Liu, Wenjing College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Laboratory of Science and Technology on Space Intelligent Control Beijing China

ISBN: (纸本)9798350303759

The prediction of the remaining useful life of the turbofan engine of an aircraft is a very important part of its PHM. With the arrival of the era of Big data, data driven RUL prediction methods are gradually emerging, however, in the actual industry, it is often difficult to collect sufficient data to predict the RUL under deep learning which means there will be a problem of small samples. Moreover, in the early stage of degradation, it is difficult to accurately classify the health status of equipment, resulting in the inability to provide early warning before the rapid degradation of equipment performance, thus losing the significance of developing maintenance strategies in advance. To solve this problem, this paper proposes a WGAN-Trans model, which expands the data set by improving the Gener-ative adversarial network, uses the one-dimensional Convolutionl Neural Network to divide the health state, and finally uses the Transformer model to predict the RUL, which is verified on the commercial aircraft turbofan engine data set provided by NASA. The results show that the proposed model has good performance. © 2023 IEEE.

关键词： Turbofan engines

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Image motion and experimental study of a 0.1″space pointing measuring instrument for micro-vibration conditions

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Chinese Journal of Aeronautics 2023年第2期36卷 191-200页

作者： Lin LI Li YUAN Li WANG Miaomiao WANG Xiaoxue GONG Jie SUI Yanpeng WU Ran ZHENG Space Optoelectronic Measurement and Perception Lab. Beijing Institute of Control EngineeringBeijing 100190China China Academy of Space Technology Beijing 100094China Science and Technology on Space Intelligent Control Laboratory Beijing 100094China University of Chinese Academy of Sciences Beijing 100049China Changchun Institute of Optics Fine Mechanics and PhysicsChinese Academy of SciencesChangchun 130033China Chang Guang Satellite Technology Co. Ltd.Changchun130102China

There exists an increasing need for Milli-Arc-Seconds(MAS)accuracy pointing measurement for current and future space *** meet the 0.1″space pointing measurement accuracy requirements of spacecraft in future,the influence of spacecraft micro-vibration on a 0.1″space Pointing Measuring Instrument(SPMI)is studied.A Quasi-Zero Stiffness Device(QZSD)with adaptive adjustment and variable stroke was ***,a series of micro-vibration experiments of the SPMI were carried *** influence of the micro-vibration generated by Guidance Navigation control(GNC)attitude control components under different attitudes on the SPMI was *** spread function of image motion in micro-vibration was also ***,the changes of image motion under the micro-vibration environment were evaluated by extracting the gray centroid of the images,and the experiment processes and results are deeply *** results show that the firstorder frequency of the QZSD system is 0.114 Hz,and it is induced by a double pendulum system;the image motion of single flywheel spinning reached 0.015 pixels;whilst the image motion reached 0.03 pixels when three flywheels are combined *** latest findings provide a beneficial theoretical and technical support for the development of spacecraft with 0·1″pointing accuracy.

关键词： Image motion Micro-vibration Milli-arc-seconds Quasi-zero stiffness device space pointing measuring instrument

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Bagging and Boosting Fine-Tuning for Ensemble Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1728-1742页

作者： Zhao, Changming Peng, Ruimin Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 China and alsowith the ShenzhenHuazhong University of Science and Technology Research Institute Shenzhen 518029 China

Ensemble learning aggregates outputs from multiple base learners for better performance. Bootstrap aggregating (bagging) and boosting are two popular such approaches. They are suitable for integrating unstable base learners with large variance and weak base learners with large bias, respectively, but not base learners with small variance and/or bias, e.g., support vector machine, regularized logistic regression, and ridge regression. This article proposes two novel ensemble-learning-based fine-tuning approaches, boosting fine-tuning (BF) and bagging and boosting fine-tuning (BBF), to fine-tune learners with small variance and/or bias for better performance. BF embeds boosting in a single hidden layer neural network. In each iteration, BF first uses the Newton's method to generate a temporary training set, and then trains a boosting learner on it. BBF combines BF and bagging. It first uses bootstrap to obtain multiple replicas of the training set, and then trains a BF learner on each replica. Extensive experiments on 46 real-world datasets demonstrated that BBF is flexible, robust, and effective, and can fine-tune many popular classifiers to achieve better generalization performance. © 2020 IEEE.

关键词： Support vector machines

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