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The Optimal Duty Cycle Model-Predictive control of PMSM Used for Satellite Payload 1

17th Annual Conference of China Electrotechnical Society, CES 2022

作者： Li, Jialin Chen, Zhen Hu, Hengzai Liu, Xiangdong Bao, Liang School of Automatic Beijing Institute of Technology Beijing100081 China Key Laboratory of Drive and Control of Servo Motion System Ministry of Industry and Information Technology Beijing100081 China State Key Laboratory of Intelligent Control and Decision for Complex System Beijing100081 China Beijing Aerospace Automatic Control Institute Beijing100854 China

ISBN: (数字)9789819904082

ISBN: (纸本)9789819904075

Model-predictive control is emerging as an advanced control strategy for its feature that the state variables can be predicted according to the math model of the control system. In the PMSM drive application, conventional model-predictive control strategy induces current ripple due to the fact that the optimal voltage vector always acts on the system for the whole control period. In order to restrain the current ripple, the idea of duty cycle control is taken into MPC by inserting a zero vector into the optimal non-zero vector and regulating the duty cycle of non-zero vector. In this paper, the optimal duty cycle FSC-MPC strategy based on two different principles is investigated. Principle A is that the estimation is equal to the reference at the end of control cycle, and principle B is that the area under trace of the estimation is equal to that of reference. The calculation of duty based on the two different principles and the flow chart of the strategy are introduced in detail. Finally, the effectiveness of the optimal duty cycle FSC-MPC is firstly verified by the simulation, and then verified by the experimental results, which is implemented on the PMSM driver of the DQ-1 satellite payload. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Model predictive control

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Stabilization of Perturbed Continuous-Time systems Using Event-Triggered Model Predictive control

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IEEE Transactions on Cybernetics 2022年第5期52卷 4039-4051页

作者： Wang, Mengzhi Sun, Jian Chen, Jie Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

In this article, event-triggered model predictive control (EMPC) of continuous-time nonlinear systems with bounded disturbances is studied. Two novel event-triggered control schemes are proposed. In the first strategy, an event-triggering condition, designed based on the state error between the actual system state and the optimal one, with an absolute threshold is considered. In the second strategy, an event-triggering condition with a mixed threshold is designed to further save the computational resources. The minimal interevent times of both event-triggered control schemes are obtained to avoid the Zeno behavior. Sufficient conditions of recursive feasibility for these two triggering strategies, which refer to the prediction horizon, the triggering level, and the disturbance bound, are obtained, respectively. Input-to-state practical stability (ISpS) of both event-triggered control systems is established without requiring the system state entering the terminal set in finite time, respectively. Finally, the numerical simulation shows the effectiveness of the proposed methods. © 2013 IEEE.

关键词： Model predictive control

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Bearing fault signal detection based on whale algorithm to optimize stochastic resonance parameters 34

Bearing fault signal detection based on whale algorithm to o...

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第34届中国控制与决策会议

作者： Huang Weichao Zhang Ganggang Faculty of automation and Information Engineering Xi'an University of Technology Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781665478977

Aiming at the problem that the traditional stochastic resonance system cannot adaptively adjust the structural parameters in the bearing fault signal detection,this paper proposes a parameter adaptive stochastic resonance bearing fault signal detection method based on the whale optimization *** method is based on the bistable stochastic resonance system model,and the structural parameters of the bistable stochastic resonance are optimized through the adaptive whale algorithm,so that the fault signal is enhanced,and the bearing fault signal detection is *** method was verified by actual bearing fault signals,and a series of comparative experiments were carried *** results show that the method in this paper has a simple model,few algorithm parameters,fast convergence speed,and a large output signal-to-noise ratio of the stochastic resonance system,which can accurately and efficiently detect bearing fault signals.

关键词： Stochastic Resonance Whale Optimization Algorithm Bearing Failure Signal

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Online Estimation of State of Healh for Lithium-ion Batteries Based on Attention-LSTM Netwrok Using Partial Charging Features 6

Online Estimation of State of Healh for Lithium-ion Batterie...

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6th International Conference on Energy, Electrical and Power Engineering, CEEPE 2023

作者： Yao, Yue Wang, Ying Zhang, Jiangfeng Zhang, Kaifeng Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China State Grid Zhejiang Electric Power Research Institute Zhejiang China

ISBN: (纸本)9798350348279

Accurate estimation for state-of-health (SOH) of lithium-ion batteries is critical to ensure the security and durability of battery operation. Accordingly, this paper proposes a SOH estimation method based on Attention-LSTM neural network using the partial charging features. First, features are extracted from partial constant-current charging curves. Second, Pearson coefficient analysis is employed to analysis the mapping relationship between extracted features and SOH. Third, an Attention-LSTM network is utilized to realize the SOH estimation. The attention mechanism can adaptively assign weights to the input features and time steps, thereby improving the estimation accuracy. Validation experiments are conducted on public dataset from NASA Ames Prognostics Center of Excellence. The experimental results highlight that the proposed method has higher accuracy and robustness compared with other approaches. © 2023 IEEE.

关键词： Lithium-ion batteries

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Solving the Collaborative Problem in the Process of Dual-Arm Robot Assembly Based on Fully Constrained Synchronous Collaboration Mode

Solving the Collaborative Problem in the Process of Dual-Arm...

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2022 Chinese Automation Congress, CAC 2022

作者： Sui, Shunfan Gan, Yahui Dai, Xianzhong Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing China

ISBN: (纸本)9781665465335

In this paper, a fully constrained collaboration synchronization model is proposed to solve the cooperative problem in the dual-arm assembly process. Compared with the single-arm robot, the dual-arm robot has higher flexibility and larger working space, but it is more difficult to control. It has its inherent constraint relationship during movement. The dual-arm cooperation constraint is the basis of the dual-arm motion planning. The paper first analyzes the constraint relationship between the two arms when the rigid body is transported by the two arms and the assembly of the shaft hole respectively. The study finds that there are many common points between the two movements: during the movement process, the two manipulators always maintain a constraint relationship with the object. On this basis, the full constraint is proposed to solve the position and pose constraints of the tool hands when the arms are moved. Finally, the simulation experiment of dual-arm handling rigid body and shaft-hole assembly is carried out to verify that the proposed dual-arm cooperation mode can effectively realize the dual-arm cooperative motion. © 2022 IEEE.

关键词： Motion planning

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Semantic Coherence Guided Multiview Similarity for Image Classification with Varied Supervision

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 3072-3082页

作者： Zhang, Chunjie Cao, Ping Bai, Huihui Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Pairwise similarity has been widely used for image classification by propagating the class information from labeled images to unlabeled images and predicting the classes of unlabeled images accordingly. Although widely used, pairwise similarity based classification methods have two drawbacks. On one hand, visual-semantic similarity consistency does not always hold due to semantic gap. On the other hand, the reliability of pairwise similarity is also influenced by the number and underlying distribution of labeled images. A well-designed classification model cannot be easily generalized to few-shot classification tasks. To solve these two problems, in this article, we propose a semantic coherence guided multiview similarity (SCG-MV) for image classification method with varied supervision levels. We measure the semantic coherence between image pairs for classifier learning. This is achieved by first conducting line search along the line segment between each image pair, and then measure the semantics of each interval. The similarity of one image pair can then be obtained by aggregating the semantic coherence of all the intervals. In this way, we can model image similarities more finely and discriminatively. To make use of multiview information, we also use the semantic coherence guided image similarities to learn multiview classifiers. The proposed semantic coherence guided method can be combined with other similarity based methods for image classification with various levels of supervision. We conduct both few-shot and fully supervised classification experiments on four datasets with the results well prove the discriminative power and generalization ability of the proposed method. © 2020 IEEE.

关键词： Semantics

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Lightweight Vision Transformer for Small Data Sets 38

Lightweight Vision Transformer for Small Data Sets

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Fang, Wenxing Su, Yanxu Institutes of Physical Science and Information Technology Anhui University Hefei China School of Artificial Intelligence Anhui University Hefei230601 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

With the rapid development of Transformers in the field of computer vision, models based on Transformers have become highly competitive architectures in the area. Although variants of Transformer models have achieved increasing accuracy on image classification tasks, the size of the training set and the number of parameters required by the models have increased dramatically. When dealing with small datasets, such models face problems such as overfitting and undergeneralization, leading to poor accuracy on the test set. We propose a new lightweight vision transformer (LVT) to address these issues. We reconstructed the backbone network, which learns the relationship between pixels through local window self-attention and global self-attention computation. We also use the attention pooling approach to fuse the token sequences generated by the backbone network more meticulously. We trained on the CIFAR-10 and CIFAR-100 datasets from scratch and compared them with a modern convolutional neural network. The experimental results show that LVT outperforms the modern convolutional neural network in terms of accuracy and efficiency. On the test set of CIFAR-10, we have obtained an accuracy of 96.83%, which indicates that our model can effectively solve the problems facing the training of small datasets and has a wide range of application prospects. © 2023 IEEE.

关键词： lightweight pooling self-attention windows

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Missing Small Bolt Detection on High-speed Train Using Improved Yolov5 8

Missing Small Bolt Detection on High-speed Train Using Impro...

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8th International Conference on systems and Informatics, ICSAI 2022

作者： Wei, Yiming Lu, Xiaobo Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing China

ISBN: (纸本)9781665474481

Tiny bolts are widely used on high-speed trains, playing an important role in fixing train components. However, because of the complex running environment of trains, missing bolts occur from time to time and may cause traffic accidents, resulting in property damage and, in serious cases, endangering the lives of the occupants. Therefore, it is essential to detect missing bolts on high-speed trains. The bolts discussed in this paper are generally located on the underside of high-speed trains and their small size makes detection more difficult. In this paper, we first expand the dataset, and then add the Attention module and Transformer based on YOLOv5, and change the FPN of YOLOv5 to BiFPN, fuse the features of different layers using different weights, and crop the high-resolution original image during training and testing, and finally return to the original image. Our method eventually achieves 95.3% AP, effectively improving the detection accuracy. © 2022 IEEE.

关键词： Statistical tests

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A Trajectory Tracking Algorithm Based on Interior Point Method for A Class of Mobile Manipulators

A Trajectory Tracking Algorithm Based on Interior Point Meth...

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2022 Chinese Automation Congress, CAC 2022

作者： Rao, Xuechen Gan, Yahui Wang, Xiaoteng Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation NanJing China

ISBN: (纸本)9781665465335

At present, due to the high redundancy and strong coupling characteristics of mobile manipulator systems, there are few and in-depth studies on coordinated motion planning. Aiming at the above problems, this paper proposes a coordinated control algorithm that can track the desired trajectory of the end-effector based on a class of 5-DOF mobile manipulators. The algorithm takes the power consumption and trajectory stability of the entire system as the optimization objectives, and sets the function of the selected optimization objective on the desired trajectory, and performs optimization based on the interior point method of convex optimization to converge to the optimal solution faster. Finally, the system is simulated to verify the correctness and effectiveness of the control algorithm. © 2022 IEEE.

关键词： Convex optimization

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Generalized Proportional Integral Observer Based Sliding Mode control for Biaxial Motion control system with Mismatched Disturbances 41

Generalized Proportional Integral Observer Based Sliding Mod...

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第41届中国控制会议

作者： Guancheng Ren Zuo Wang Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex systems of Engineering Ministry of Education Shenzhen Research Institute Southeast University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In the biaxial motion system,nonlinearities and mismatched disturbances always have adverse effects on the contouring accuracy,which are often *** of existing advanced control methods are developed only to suppress matched *** this paper,the necessity of taking the contour error as the control target is ***,four generalized proportional integral observers(GPIOs) are developed to estimate both matched and mismatched lumped ***,based on contour error,a sliding mode controller is developed for the biaxial motion *** introducing the disturbance estimations into the modified sliding surface design,a composite controller is *** proposed method effectively improves the contouring accuracy and suppress the mismatched disturbances,while the chattering caused by large switching gains is *** stability analysis of the system is established by means of the Lyapunov ***,to demonstrate the superiority and effectiveness of the controller,simulation results of the biaxial motion control system are presented in various working cases.

关键词： Biaxial motion control system contouring control mismatched disturbances generalized proportional-integral observer(GPIO) sliding mode control chattering reduction

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