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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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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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A novel kind of sufficient conditions for safety judgement based on control barrier function

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Science China(Information Sciences) 2021年第9期64卷 264-266页

作者： Zheren ZHU Yi CHAI Zhimin YANG Key Laboratory of Complex System Safety and Control (Chongqing University) Ministry of Education School of Automation Chongqing University

Dear editor,Recently, work safety accidents have started to occur on a large scale in Chinese petrochemical companies. Further,the operational safety of large and complex systems is being closely monitored by our government, environmental organizations,and conscientious citizens. The scale of complex systems, such as industrial systems and smart grids,

关键词： safety criterion control barrier function fault safety complex system sufficient condition

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Deep Multimodal Learning and Fusion Based Intelligent Fault Diagnosis Approach

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Journal of Beijing Institute of Technology 2021年第2期30卷 172-185页

作者： Huifang Li Jianghang Huang Jingwei Huang Senchun Chai Leilei Zhao Yuanqing Xia Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of TechnologyBeijing 100081China

Industrial Internet of Things(IoT)connecting society and industrial systems represents a tremendous and promising paradigm *** IoT,multimodal and heterogeneous data from industrial devices can be easily collected,and further analyzed to discover device maintenance and health related potential knowledge *** data-based fault diagnosis for industrial devices is very helpful to the sustainability and applicability of an IoT *** how to efficiently use and fuse this multimodal heterogeneous data to realize intelligent fault diagnosis is still a *** this paper,a novel Deep Multimodal Learning and Fusion(DMLF)based fault diagnosis method is proposed for addressing heterogeneous data from IoT environments where industrial devices ***,a DMLF model is designed by combining a Convolution Neural Network(CNN)and Stacked Denoising Autoencoder(SDAE)together to capture more comprehensive fault knowledge and extract features from different modal ***,these multimodal features are seamlessly integrated at a fusion layer and the resulting fused features are further used to train a classifier for recognizing potential ***,a two-stage training algorithm is proposed by combining supervised pre-training and fine-tuning to simplify the training process for deep structure models.A series of experiments are conducted over multimodal heterogeneous data from a gear device to verify our proposed fault diagnosis *** experimental results show that our method outperforms the benchmarking ones in fault diagnosis accuracy.

关键词： fault diagnosis deep learning multimodal heterogeneous data multimodal fused features

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An Indoor Positioning Algorithm Against NLOS Error Based on UWB 41

An Indoor Positioning Algorithm Against NLOS Error Based on ...

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第41届中国控制会议

作者： Mingxiang Liao Yongbo Li Guangyao Wang Zhenyu Lei Zihao Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems System Integration and Industrial Robotics Laboratory

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Ultra-wideband（UWB） positioning technology has absolute advantages due to its centimeter-level accurate positioning ***,the positioning accuracy is greatly reduced because of the inability to completely solve the error caused by non-line-of-sight（NLOS） and multi-path *** present,the Chan-Taylor（C-T） combination algorithm proposed by scholars can achieve a good positioning effect in the line-of-sight（LOS） environment,but in the NLOS environment,positioning deviation of this algorithm is large .Aiming at the problem of low localization accuracy in NLOS environment,this paper presents a Chan-Taylor-Kalman（CTK） joint positioning algorithm based on UWB and adapted to NLOS *** basic idea of CTK joint positioning algorithm is to introduce weight coefficients on the basis of C-T combination algorithm to reduce the situation of non-convergence of positioning results;then combined with the improved Kalman filter to eliminate outliers and eliminate the influence of the non-line-of-sight *** show that under the same NLOS environment,the probability of the positioning error of the C-T combination positioning algorithm greater than 20 cm is about 60%,while the probability of the positioning error of the CTK joint positioning algorithm greater than 10 cm is only about 10%.

关键词： UWB NLOS indoor positioning Chan-Taylor combination algorithm Kalman filter

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Research on optimization of two-stage scheduling for aluminum extrusion machine manufacturing line

Research on optimization of two-stage scheduling for aluminu...

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2024 China Automation Congress, CAC 2024

作者： Zhou, Aoran Qiu, Lipeng Wu, Yali Department of Information and Control Engineering Xi'an University of Technology Shaan'xi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co Ltd Xi'an710016 China

ISBN: (纸本)9798350368604

In view of the problems of high energy consumption, long inventory time and low production efficiency in the production process of traditional aluminum extrusion machine, this paper establishes an efficient two-stage parallel scheduling optimization model based on the integration of flexible job shop scheduling and assembly sequence planning (IFJSS-ASP). On this basis, an evolutionary algorithm combining strong dominance relationship and simple grouping method (SDREA-SGM) is proposed. The algorithm utilizes a two-stage hybrid chromosome encoding and decoding method to establish a rational mapping from the decision space to the solution space. Furthermore, in order to prevent the model from easily falling into local optima, an adaptive intra-class and inter-class pairing selection strategy has been adopted by the algorithm. This enhances global search and improves local search ***, the feasibility and effectiveness of the algorithm are verified by solving problems of different scales. © 2024 IEEE.

关键词： Job shop scheduling

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Cooperative Resource Allocation for NOMA-MEC Multi-Cell Network

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IEEE Transactions on Vehicular Technology 2025年第6期74卷 9027-9042页

作者： Cai, Yujin Zhang, Zaichen Huang, Yongming Yu, Wenwu Nie, Xiaokai Liu, Hongzhe Southeast University School of Mathematics Jiangsu Nanjing211189 China Southeast University National Mobile Communications Research Laboratory Nanjing211189 China Purple Mountain Laboratories Nanjing211111 China Southeast University School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518057 China

Integrating non-orthogonal multiple access (NOMA) and mobile edge computing (MEC) enables IoT nodes to offload their complicated tasks to MEC servers. Most of the existing resource allocation schemes in NOMA-MEC networks are based on the centralized optimization framework, which may increase the communicational and computational burden on the central unit. In this paper, the NOMA-MEC multi-cell network without the central unit is considered. To minimize the task completion time and offloading cost, a joint optimization problem including sub-channel allocation, transmit power, offloaded proportions, computing frequencies of IoT nodes and MEC servers, and price of MEC resources is investigated. In order to tackle the formulated mixed integer nonlinear programming problem, a two-stage low-complexity distributed algorithm based on the cooperation of all base stations (BSs) is proposed. Specifically, in Stage 1, a distributed heuristic sub-channel allocation algorithm is designed based on the sub-channel gains. In Stage 2, with the obtained sub-channel allocation result, a cooperative distributed continuous variable optimization algorithm is devised based on the distributed optimization and alternating optimization methods. Numerical results demonstrate the convergence of the proposed two-stage algorithm for three interference cases. Besides, the impacts of system parameters and schemes on the network performance are analyzed. More importantly, the resource allocation time can be significantly shortened by employing the cooperation of BSs compared with the centralized algorithm © 1967-2012 IEEE.

关键词： Nonlinear programming

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Anti-disturbance Low Speed Regulation control of PMSMs Using Modified Extended State Observer Based on Rotor Position

Anti-disturbance Low Speed Regulation Control of PMSMs Using...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Xu, Lei Mao, Linxuan Li, Shihua School of Electronic Science and Engineering Southeast University Nanjing210096 China School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

A modified extended state observer (ESO) based rotor position algorithm is proposed for improving low speed regulation control performance. The speed signal is often obtained by differentiating the position signal. However, the position signal of encoder with quantization errors results in crawling and shaking at low speeds. Considering quantization error as a type of noise limited their own accuracy, the environmental influences like mechanical vibration and electromagnetic interference also lead to noise in rotor position. The modified ESO method incorporated a Kalman filter (KF) is proposed to reduce the negative impact of noise. Due to differential amplification noise, the position signal is used instead of traditional speed signal for observers design because of its undesirable characteristics at low speed. The modified ESO based on rotor position is used to estimate both speed signal and disturbances to enhance the low speed performance in the presence of disturabances and measurement noise. The friction model is embedded for above integrated structure due to its nonliearity at low speeds. Considering the negative effects of measurement noise and disturbance at low speeds, it has verified that the proposed algorithm has better dynamic and steady-state performance and anti-disturbance ability through simulation. © The Institution of Engineering & Technology 2024.

关键词： State estimation

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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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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