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Data-driven control of consensus tracking for discrete-time multi-agent systems

Journal of the Franklin Institute 2023年第7期360卷 4661-4674页

作者： Xiufeng Zhang Gang Wang Jian Sun Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Kunming 650504 China Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming 650504 China School of Automation Beijing Institute of Technology Beijing 100081 China Key Lab of Intelligent Control and Decision of Complex Systems Beijing 100081 China

This paper investigates the consensus tracking problem of leader-follower multi-agent systems. Different from most existing works, dynamics of all the agents are assumed completely unknown, whereas some input-output data about the agents are available. It is well known from the Willems et al. Fundamental Lemma that when inputs of a linear time-invariant (LTI) system are persistently exciting, all possible trajectories of the system can be represented in terms of a finite set of measured input-output data. Building on this idea, the present paper proposes a purely data-driven distributed consensus control policy which allows all the follower agents to track the leader agent’s trajectory. It is shown that for a linear discrete-time multi-agent system, the corresponding controller can be designed to ensure the global synchronization with local data. Even if the data are corrupted by noises, the proposed approach is still applicable under certain conditions. Numerical examples corroborate the practical merits of the theoretical results.

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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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Chinese Automation Congress (CAC)

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

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

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 flexibility. Finally, the feasibility and effectiveness of the algorithm are verified by solving problems of different scales.

关键词： Energy consumption Job shop scheduling Optimization models Aluminum Production Evolutionary computation Encoding Planning Decoding Optimization

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Temperature control system of Thermoelectric Cooler Based on Improved ADRC

Temperature Control System of Thermoelectric Cooler Based on...

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Chinese control and decision Conference, CCDC

作者： Xiyuan Shan Tao Cai Zhicheng Zong Hongbo Mu School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781665478977

Aiming at the problems containing complex working conditions, modeling difficulties and long-time delay of thermoelectric cooler temperature control system, an improved ADRC control method combining ADRC and Smith predictor is proposed in this paper. ADRC deals with the disturbances and uncertain dynamics in the system, SP compensates the time delay to improve the control performance. Compared with the traditional PID controller, the proposed control method has faster response speed and stronger anti-disturbance ability, meanwhile, overcomes the dependence of Smith predictor on object parameters to a certain extent. Through simulation and experimental verification, a good control effect is obtained, which provides a positive guidance of the related application of thermoelectric cooler.

关键词： Robust control Employee welfare Delay effects Simulation Perturbation methods Predictive models control systems

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Fault Diagnosis for Small Samples Based on VMR

Fault Diagnosis for Small Samples Based on VMR

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Chinese Automation Congress (CAC)

作者： Xuejin Wu Yanghu Hu Yali Wu Department of Information and Control Engineering Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd Xi'an China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

The scarcity of fault samples presents a significant challenge for fault diagnosis in industrial processes. Conventional methods often fail to deliver satisfactory results when dealing with small sample sizes. In addressing the issue of small sample fault diagnosis in industrial processes, this paper utilizes the Variational Mode Reconstruction(VMR) algorithm to screen the best components decomposed by the Variational Mode Decomposition(VMD) through the envelope entropy then random weighting them and signal reconstruction to achieve data enhancement, to enrich the sample size and to prevent the model overfitting phenomenon due to the scarcity of samples. Meanwhile, this paper integrates Convolutional Neural Network (CNN) and Long Short-term Memory Neural Network (LSTM) to propose a network model of spatio-temporal feature fusion for feature extraction and classification. The experiments demonstrate that this model not only enhances data diversity but also ensures consistency before and after enhancement, effectively mitigating overfitting. Furthermore, it guarantees high recognition and generalization rates in fault diagnosis.

关键词： Fault diagnosis Training Neural networks Rolling bearings Feature extraction Data models Signal reconstruction Convolutional neural networks Long short term memory Overfitting

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An Improved Active Disturbance Rejection control Method for Crane system

An Improved Active Disturbance Rejection Control Method for ...

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Chinese control and decision Conference, CCDC

作者： Yubo Sun Xiyuan Shan Zhicheng Zong School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781665478977

In order to improve the dynamic performance of the underdriven crane system, an improved linear active disturbance rejection controller (LADRC) based on the new error was proposed. The improved LADRC takes the error value between the disturbance and its observed value multiplied by a coefficient as the basis for adjusting the linear extended state observer (LESO). The improved method has two advantages. Firstly, the new error can prevent the traditional LESO from choosing larger parameter adjustment disturbances, which will limit the performance of the observer. Secondly, the pole can be configured by adjusting the coefficient to obtain better dynamic characteristics. Finally, the effectiveness of the proposed method is verified by simulation and experiment. The proposed method can effectively restrain the swing of the payload and it is robust to system parameters perturbation as well.

关键词： Robust control Couplings Adaptation models Cranes Uncertainty Perturbation methods Bandwidth

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An Optimized One-Stage Detector for Autonomous PV Defect Detection

An Optimized One-Stage Detector for Autonomous PV Defect Det...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Huidi, Xiao Jiajia, Zhao Lihui, Wang Qiucheng, Shen Nongjie, Ma Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education School of Instrument Science and Engineering Southeast University Nanjing210096 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China School of Mechanical and Electronic Control Engineering Beijing Jiaotong University Beijing China

ISBN: (纸本)9789811694912

To realize the defect detection of Photovoltaic (PV) modules based on infrared images, a one-stage detector based on FPT and loss function optimization is proposed. Firstly, ResNet50 is selected as the backbone network for feature extraction, combining with the idea of migration learning to strengthen its feature extraction ability. Besides, replacing the traditional feature pyramid with FPT, using Transformer structure help realize the interaction of the same position between different pyramid layers as well as different positions of the same layer, improving the feature fusion capability of the model. Finally, to alleviate the problem of suppression of non-optimal predictions by NMS strategy, a bipartite graph matching algorithm based on loss function minimization is designed to enhance the learning of the distribution of ground truth targets by the network. The dataset is expanded by Mosaic data enhancement method for model training, so as to achieve infrared image-based PV defect detection. Results show that the improved one-stage target detection network has a promising detection effect on PV module defects under infrared images, with the average accuracy improving by 2.20% compared with the original algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Defects

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GAT-Net: A Network using Grid Attention and Transformer for Dynamic Facial Expression Recognition

GAT-Net: A Network using Grid Attention and Transformer for ...

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Chinese control and decision Conference, CCDC

作者： Wenxin Dai Yaping Dai Kaoru Hirota Shuai Shao School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781665478977

Dynamic facial expression recognition (DFER) in the wild has received widespread attention recently. There are complex factors such as face occlusion and pose variation in the wild. Facial expression recognition has a subtle competition between capturing local features of a human face and obtaining a global feature representation. This paper proposes an end-to-end DFER network GAT-Net based on the grid attention module and Transformer, which improves the robustness and accuracy of DFER in the wild. Specifically, GAT-Net is divided into two components: spatial feature extraction and temporal feature processing. The grid attention module of the spatial feature extraction component guides the network to pay attention to the local salient features of the face, which reduces the interference of field occlusion and non-frontal poses. The Transformer in the temporal feature processing component guides the network to learn the temporal relationship of high-level semantic features and the global representation of facial expression features. These two components balance the subtle competition between local features and global feature representations of facial expressions. The ablation experiment has proved the effectiveness of the grid attention module and Transformer. Experiments demonstrate that our GAT-Net outperforms state-of-the-art methods on DFEW and AFEW benchmarks with accuracies of 67.53%, and 50.14% respectively.

关键词： Face recognition Semantics Interference Benchmark testing Transformers Feature extraction Robustness

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Design of a Novel Autonomous Docking system With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

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Dual and reduced-order observer based attack-free protocols for consensus of multi-agent systems with Markovian switching topologies

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systems and control Letters 2025年 202卷

作者： Gao, Tian-Yu Li, Zhao-Yan Zhou, Bin Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China School of Mathematics Harbin Institute of Technology Harbin150001 China Zhengzhou Research Institute of HIT Zhengzhou450000 China

This paper studies the output feedback consensus problem of linear multi-agent systems with Markovian switching topologies. To avoid reconstructing the Markovian switching topologies during designing the observers or adding the state of the observers to the information exchange loop, dual and reduced-order observer based attack-free consensus protocols are proposed, which only utilizes the relative outputs of neighboring agents. It is shown that, under certain mild conditions, a necessary and sufficient condition for the solvability of the mean square consensus problem is that the union of switching topologies has a spanning tree. Finally, numerical examples are given to illustrate the effectiveness of the proposed approaches. © 2025 Elsevier B.V.

关键词： Markov processes

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Resource Scheduling Base on Bayesian Cramer-Rao Lower Bound for Multi-Target Tracking in Netted Colocated MIMO Radar systems

Resource Scheduling Base on Bayesian Cramer-Rao Lower Bound ...

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第40届中国控制会议

作者： Sijian Liao Zhihong Peng Junqi Cai School of Automation Beijing Institute of Technology China State Key Laboratory of Intelligent Control and Decision of Complex System

In this paper, an effective joint beam selection and power allocation（JBSPA） method is proposed to solve the online resource scheduling problem for multi-target tracking in distributed MIMO radar system. Overall target tracking performance can be improved by optimizing radar system beam selection and power allocation, since each MIMO radar can generate a timevarying beam, and adjust the quality of the observed signal by controlling the transmit power of each beam. In our method the feedback information of the target tracking period is used to complete the optimal radar-targets assignment and power allocation,the objective function is formulated based on the Bayesian Cramér-Rao lower bound, as the formulated JBSPA problem is nonconvex, a three steps solution method based on reward matrix is proposed to solve it effectively. Numerical results show that the proposed JBSPA method can deliver better performance than the competitors in overall MTT performance.

关键词： Resource Scheduling BCRLB Target Tracking Power Allocation MIMO Radar systems

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