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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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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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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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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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Composite Model Predictive control for PMSM Servo Systems Based on Backlash Cancellation and Disturbance Compensation 41

Composite Model Predictive Control for PMSM Servo Systems Ba...

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第41届中国控制会议

作者： Lei Li 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

This paper investigates the speed regulation problem of permanent magnet synchronous motor(PMSM) servo system with backlash based on model predictive control(MPC).It is known that the existing backlash in servo systems causes steady-state errors,limit cycles and rigid *** order to counteract the adverse performance degradations of the backlash nonlinearity,a composite MPC strategy is investigated based on backlash cancellation and disturbance ***,an approximated dead-zone model of backlash is ***,a generalized proportional-integral observer(GPIO) is constructed to estimate the lumped disturbances,including backlash modelling residual error,parameter uncertainties and external *** introducing disturbance estimation and backlash transmission torque into system model,a composite MPC can be obtained based on the prediction-precision enhanced model,which brings significantly improvements to control ***,the efficacy of the presented method is demonstrated by simulation results.

关键词： Model predictive control(MPC) PMSM servo system Backlash cancellation Generalized proportional-integral observer(GPIO)

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Inverse Reinforcement Learning Integrated Reinforcement Learning for Single Intersection Traffic Signal control 5

Inverse Reinforcement Learning Integrated Reinforcement Lear...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Gu, Shiyi Zhang, Tingting Zhang, Ya Southeast University School of Automation Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China Army Engineering University College of Command and Control Engineering Nanjing210017 China

ISBN: (纸本)9798350325294

Traffic Signal control (TSC) optimization is vital for efficient traffic flow in urban intersections. Recent research has explored the application of Reinforcement Learning (RL) agents to tackle TSC challenges. However, the selection of an appropriate reward function in RL agent training still relies on subjective judgment and experience. To address this issue, an Inverse Reinforcement Learning (IRL) integrated RL algorithm is proposed. In the IRL learning section, expert trajectory data are collected and analyzed by Relative Entropy IRL (REIRL). The latent reward of expert policy is reconstructed and utilized in RL agent training process. In the RL control section, a Double Dueling Deep Q Network is applied under a cycle control framework. As verified in simulations, the introduction of expert experience improves the performance of the RL agent to the expert level and concurrently enables robustness to expert policy noises. © 2023 IEEE.

关键词： Reinforcement learning

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Multi-task Learning Based Single Temporal Remote Sensing Image Change Detection 23

Multi-task Learning Based Single Temporal Remote Sensing Ima...

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Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition

作者： Peixuan Yang Yichao Cao Xiaobo Lu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University China

ISBN: (纸本)9798400707988

Change Detection is a classic and fundamental task in remote sensing(RS), and has accomplish remarkable achievement on bitemporal image based methods. However, bitemporal images are very expensive and needs professional researchers to align and label the paired images. Furthermore, most bitemporal image based methods are only semantic-aware not instance-aware, which indicates these methods only use paired images’ semantic information. Thus, we propose a method that only needs unpaired RS images with semantic labels. In this paper, we introduce multi-task learning into change detection progress, which comprises four major parts: Boundary-Aware Module, Contextual-Aware Module, Segmentation Module, Change Detection Module. At first, we construct Boundary-Aware Module and Contextual-Aware Module to extract sharp boundary and dense contextual features. Then we feed the feature maps to Change Detection Module and Segmentation Module to accomplish the subtasks. The comprehensive experiments on a single temporal image dataset demonstrate the efficiency of our approach over other bitemporal image based methods, and the experimental results shows our approach is competitive with other methods while all methods was trained on bitemporal image dataset.

关键词： Change Detection Multi-task Learning Single Temporal Image

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Equivalent Ratio of Frequency Regulation Resources Based on Derivation of Open-Loop control Frequency Deviation 16

Equivalent Ratio of Frequency Regulation Resources Based on ...

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16th IEEE PES Asia-Pacific Power and Energy engineering Conference, APPEEC 2024

作者： Ning, Jia Wang, Hanxiang Wang, Ying School of Electric Power Engineering Nanjing Institute of Technology Nanjing China Southeast University Key Laboratory of Measurement and Control of Cse Ministry of Education Nanjing China

ISBN: (纸本)9798350386127

The conventional approach to frequency regulation predominantly relies on thermal and hydroelectric power generation units. As a growing variety of frequency regulation resources become accessible to power systems, there is significant variation in their performance characteristics, it is important to quantify their capabilities in the frequency service markets. This study introduces a technique to calculate the equivalent ratio of these resources by analyzing their primary response to frequency deviations derived from open-loop control. Based on the rotor motion equation of the generator, this paper constructs a load frequency control model incorporating two distinct regulation resources, linearize their outputs, and integrate them into the model. Through differential equations, this paper derives analytical expressions for the frequency deviation curve, enabling the determination of key frequency metrics. The equivalent ratio is then calculated by comparing the output power of resources with similar performance indicators. Finally, the paper investigates the impact of diverse parameters on the computation of the equivalent ratio employing simulation-based experimental analysis. © 2024 IEEE.

关键词： Open loop control

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Group Hybrid Coordination control of Multi-Agent Systems With Time-Delays and Additive Noises

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 737-748页

作者： Chuanjian Li Xiaofeng Zong School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China IEEE

A new kind of group coordination control problemgroup hybrid coordination control is investigated in this *** group hybrid coordination control means that in a whole multi-agent system(MAS)that consists of two subgroups with communications between them,agents in the two subgroups achieve consensus and containment,*** MASs with both time-delays and additive noises,two group control protocols are proposed to solve this problem for the containment-oriented case and consensus-oriented case,*** developing a new analysis idea,some sufficient conditions and necessary conditions related to the communication intensity betw een the two subgroups are obtained for the following two types of group hybrid coordination behavior:1)Agents in one subgroup and in another subgroup achieve weak consensus and containment,respectively;2)Agents in one subgroup and in another subgroup achieve strong consensus and containment,*** is revealed that the decay of the communication impact betw een the two subgroups is necessary for the consensus-oriented ***,the validity of the group control results is verified by several simulation examples.

关键词： Additive noises consensus control containment control group hybrid coordination control multi-agent systems(MASs) time-delays

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A nested constraints based anti-disturbance collision-free formation control scheme for multi-mobile robot systems

A nested constraints based anti-disturbance collision-free f...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Guodong Wang, Xiangyu Li, Shihua Niu, Dan Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing210096 China

ISBN: (纸本)9781665465335

This paper investigates distributed formation control of multi-mobile robot systems with collision avoidance. A novel nested constraints based anti-disturbance formation control scheme is established, which contains two parts. In the first part, a formation signal generator is constructed on the communication network by using proper distributed cooperative control approaches and artificial potential field-based methods, such that it "completes"the desired formation control task in its outputs. In the second part, by combining proper disturbance estimations, some nonlinear tracking controllers are designed for the robots to track the corresponding outputs of the generator asymptotically. A "nested constraint mechanism"is put forward accordingly and applied to limit the generator's outputs and the robots' tracking errors. In this way, the studied multi-mobile robot systems realize the formation control goal with collision avoidance. Compared with existing results, the proposed method has a better plug-and-play feature to deal with the tight encapsulations of the practical robot products, and has better convergence performances with the existence of disturbances. Some experiments are given to validate the effects of the proposed methods. © 2022 IEEE.

关键词： Collision avoidance

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