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12th International Conference on CYBER Technology in automation, control, and intelligent Systems, CYBER 2022

作者： Du, Jingbo Jiang, Yong Shenyang Ligong University Shenyang110158 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aiming at the problem that the substation insulator replacement robot cannot accurately identify insulator pins in the complex outdoor light environment, an improved YOLOv5-based insulator pin identification method YOLOv5-CBP is proposed. For the substation insulator pin recognition task, the backbone of the network is replaced by the lightweight EfficientNet-lite0;the Neck of the network is optimized and a more efficient feature fusion module BiFPN combined with an attention mechanism is introduced. The bounding box regression loss function was changed to improve the accuracy of inspection frame detection. Finally, the improved algorithm is compared with the original YOLOv5 algorithm on a self-built dataset for experiments. The results show that the insulator pin recognition accuracy is improved by 8.3%, the size of the algorithm model is reduced to 54% of the original, and the number of parameters is reduced by 49.4%. The improved algorithm model more lightweight. © 2022 IEEE.

关键词： Degradation Substations Inspection Insulators control systems Pins Neck

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Generalized Optimization Approach to Design In-Plane Distributed Compliant Remote Center of Motion Mechanism

SSRN

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SSRN 2024年

作者： Zhang, Zhaowei Pieber, Michael Gerstmayr, Johannes State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Nanta Street 114 Liaoning Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences No.135 Chuangxin Rd Liaoning Shenyang110169 China Department of Mechatronics University of Innsbruck Technikerstraße 13 Innsbruck6020 Austria

Remote center of motion (RCM) mechanisms are widely used because their center of rotation is outside the mechanical device. Usually, compliant RCM mechanisms use a linkage-based design with flexure hinges to achieve relative motion. It is still an open question to design a distributed compliant RCM mechanism using flexural beams. Addressing this, the paper proposes a generalized optimization approach for the design. The optimization approach is implemented in two steps. First, we use beams to establish a dual-layer ground structure. Using a genetic algorithm and considering the relative density of beams as variables, we obtain the optimized topology. Second, based on the topology and employing curved beams for size-shape optimization, we achieve optimized distributed compliant RCM mechanisms. Based on this approach, we explore and identify four distinct topologies and four detailed distributed compliant RCM mechanisms. With the comparison of stiffnesses and rotational axis shift, two kinds of optimized distributed compliant RCM mechanisms are considered. For verification, commercial finite element method software ABAQUS were used, demonstrating excellent alignment. Ultimately, this approach can be generalized for optimizing distributed compliant RCM mechanisms. © 2024, The Authors. All rights reserved.

关键词： Topology

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Research on Industrial control Network Security Measurement Method Based on GRU-SVM

Research on Industrial Control Network Security Measurement ...

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2022 Chinese automation Congress, CAC 2022

作者： Chen, Hengfei Liu, Xianda Sheng, Chuan Pan, Hao College of Information Engineering Shenyang University of Chemical Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665465335

Since the industrial Internet entered people's field of vision, industrial control network security has gradually received attention. Traditional network security measurement methods rely on the accuracy of situation sequences and historical situation values, and various factors in the network have a great influence on the results. However, compared with industrial control networks, the number and types of affected factors are less than those of the modern Internet. Therefore, based on the research on network security situational awareness, this paper proposes an industrial control network security measurement method model based on GRU-SVM. First, the data sets with threat type labels are classified, and then the similarity scoring mechanism and softmax function are introduced, to process the classification results. For the GRU-SVM classification module, the analysis of the simulation results shows that the convergence is better and the robustness is stronger. For the safety prediction measurement part, by comparing with different models, the mean absolute error and root mean square error are smaller and the reliability is higher. © 2022 IEEE.

关键词： Network security

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive Systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Zibo Miao Yu Pan Qing Gao Guangdong Key Laboratory of Intelligent Morphing Mechanisms School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique.

关键词： Perturbation methods Design methodology Quantum optics Robustness Feedback control Closed loop systems Tuning Cybernetics

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A New Recursive Composite Adaptive controller for Robot Manipulators

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Space(Science & Technology) 2021年第1期2021卷 77-83页

作者： Jianfei Li Yaobing Wang Zhiyong Liu Xin Jing Chengwei Hu The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications Beijing Institute of Spacecraft System EngineeringBeijing 100094China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

In this paper,a new recursive implementation of composite adaptive control for robot manipulators is *** investigate the recursive composite adaptive algorithm and prove the stability directly based on the Newton-Euler equations in matrix form,which,to our knowledge,is the first result on this point in the *** proposed algorithm has an amount of computation O(n),which is less than any existing similar algorithms and can satisfy the computation need of the complicated multidegree *** manipulator of the Chinese Space Station is employed as a simulation example,and the results verify the effectiveness of this proposed recursive algorithm.

关键词： Robot manipulators robot

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RHNet: A Real-Time High-Resolution Network for Surface Defect Detection

RHNet: A Real-Time High-Resolution Network for Surface Defec...

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第43届中国控制会议

作者： Yijie Wang Zhigang Ren Jianpu Cai Zongze Wu Shengli Xie School of Automation Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangdong University of Technology Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangdong University of Technology College of Mechatronics and Control Engineering Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)Shenzhen University Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing (GDUT) Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the industrial domain, surface defect detection after multiple processing steps is crucial for improving the outgoing quality of products. However, due to the characteristics of surface defects, such as low contrast, irregular shapes, small and elongated features, and significant noise. To address these issues, this paper proposes a novel real-time high-resolution network(RHNet). Unlike previous models, RHNet emphasizes the importance of modeling spatial information to capture small ***, the output feature maps of each module are maintained at 1/4 resolution of the original image. We introduce a short-term dual-branch module(SDBM) to handle real-time processing of high-resolution feature maps. Additionally, FPAPPM is proposed for swift extraction of deep information and multi-scale context. Through extensive experiments, we demonstrate that our proposed model exhibits robust defect modeling capabilities and detection performance while still meeting real-time requirements.

关键词： Surface defect inspection Anomaly detection Semantic segmentation Deep learning Pattern recognition

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Dimension Reduction for Dynamic Analysis of Gene Expression Data Using Variational Autoencoder

Dimension Reduction for Dynamic Analysis of Gene Expression ...

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IEEE International Conference on Cyber Technology in automation, control, and intelligent Systems

作者： Shuai Yuan Shipeng Chen Yongliang Yang School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Liaoning China

Single-cell RNA sequencing technology captures gene expression at the whole-genome scale and single-cell level in many cells. Thus, the cellular states during a physiological process would be captured in detail. These data provide new opportunities and challenges for systems biology. Previously, the models in systems biology dealt with the dynamics of specific signaling pathways. However, it is almost impossible to directly model the dynamics of the whole genome due to the ultrahigh dimensionality of the data. Here, to model its gene regulatory dynamics, the dimensionality of the whole genome was reduced significantly using the latent space of a variational autoencoder, a generative deep learning model. In the low-dimensional latent space, an ordinary differentiation equation (ODE) system has been established to analyze the dynamic characteristics of the whole genome system. To demonstrate the effectiveness of this method, we generated a low-dimensional representation of a systems biology model we previously developed. The variational autoencoder reduced the dimension from 13 to 2 in latent space. An ODE model was developed to analyze the dynamics of this two-dimensional system. The results indicated that the 2-dimensional model captured the essence of the original systems biology model.

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WindowMixer: Intra-Window and Inter-Window Modeling for Time Series Forecasting

arXiv

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arXiv 2024年

作者： Liu, Quangao Li, Ruiqi Jiang, Maowei Yang, Wei Liang, Chen Pang, LongLong Zou, Zhuozhang Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shengyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China University of Chinese Academy of Sciences China

Time series forecasting (TSF) is widely applied in various fields such as economic forecasting, weather prediction, traffic flow analysis, and public health surveillance. The core of TSF is to capture the underlying temporal patterns in the data. However, real-world time series data exhibit complex temporal patterns and may include additional noise, outliers, missing values, etc., making accurate forecasting highly challenging. Current mainstream methods typically naively treat each time point as an isolated entity, attempting to model point-to-point relationships and uncover temporal patterns within the data, which has limitations when dealing with complex time series data. Specifically, point-by-point modeling fails to take advantage of the abundant contextual information in time series data. This results in a reduced ability to capture temporal patterns and an increased susceptibility to noise. To address these issues, we examine temporal variations from a window-based perspective and present the WindowMixer model, which is built on an all-MLP framework. WindowMixer stems from a simple observation: Time series are recorded in a continuous manner, and the information at any given time point relies on the preceding and succeeding time points for a complete representation. WindowMixer decomposes time series into trend and seasonal components via a sequence decomposition and fusion architecture, handling them individually. For the trend component, we employ a straightforward fully connected (FC) layer to make predictions. For the seasonal component, we first introduce a time window at each time point and project each time window to produce window tokens. Then, we apply the Intra-Window-Mixer and Inter-Window-Mixer to further process these tokens. The Intra-Window-Mixer models relationships within each window token, while the Inter-Window-Mixer models relationships between window tokens. These dual modules allows us to capture more intricate patterns and long-range de

关键词： Time series

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Key Parameters Prediction for intelligent control and Energy Optimization Based on MIC-BWO-XGBoost 2

Key Parameters Prediction for Intelligent Control and Energy...

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2nd International Conference on Cyber-Energy Systems and intelligent Energy, ICCSIE 2024

作者： Lv, Changyao Wang, Yaqi Chen, Yudong Yu, Zhuo Hu, Guoliang Wu, Hongliang Li, Shuai Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China College of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China Shanghai Aircraft Manufacturing Co. Ltd. Shanghai201324 China

ISBN: (纸本)9798350373318

In the aviation industry, anodic oxidation serves as a core process for surface modification of aluminum alloy components, albeit accompanied by high energy consumption. Accurate prediction of key parameters can offer decision support for the intelligent control and energy optimization of anodic oxidation. However, the limited sample size resulting from the high cost of data collection and the complex nonlinear patterns caused by the synergy of multiple factors pose a challenge in accurately predicting key parameters. Therefore, we propose a key parameters prediction method based on the Maximum Information Coefficient (MIC), Beluga Whale Optimization algorithm (BWO), and XGBoost algorithm. Considering the adverse impact of low correlation parameters on prediction accuracy, we first use MIC to extract features from the original data. Then, XGBoost is used to integrate multiple decision trees to ensure the strong fitting ability for nonlinear relationships. Compared to deep learning models, XGBoost performs well even in a limited sample size. In addition, considering XGBoost is prone to overfitting training data as an ensemble learning algorithm, we employ the BWO to optimize four key parameters of the model that are difficult to choose, thereby enhancing model's generalization. The model's performance is evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with values of 0.04388, 0.09410, and 0.20730%, respectively. The experimental results demonstrate that the proposed method outperforms traditional approaches, enabling precise prediction of key parameters and holding significant value for the intelligent control and energy optimization of anode oxidation processes. © 2024 IEEE.

关键词： Anodic oxidation

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Low-noise analysis and design for the sensing system of the nanomanipulation robot by AFM

Low-noise analysis and design for the sensing system of the ...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yuan, Shuai Wu, Boyu Wang, Kaixuan Yu, Peng School of Information & Control Engineering Shenyang Jianzhu University Liaoning Province Shenyang110168 China Shenyang Jianzhu University Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665481090

In this paper, through the noise analysis of the signal processing circuit of the photoelectric sensor, two noise reduction methods are proposed by reducing the feedback resistance of the transimpedance amplifier and integrating the overall signal processing circuit. These two noise reduction methods can reduce noise and improve the signal-to-noise ratio while ensuring that the topography signal of the item is unchanged. To verify the method in this paper, the scanning head design was optimized, the feasibility of the proposed scheme was verified by the thermal noise method and the 0-range scanning method, and finally, the roughness specification was analyzed. © 2022 IEEE.

关键词： Operational amplifiers

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