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An overview on GNSS carrier-phase time transfer research

Science China(Technological Sciences) 2020年第4期63卷 589-596页

作者： ZHANG Ming Lü JinHu BAI ZhengDong JIANG ZhiQi CHEN BoBo The Key Laboratory of Systems and Control Institute o f Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Institute of Geomatics of Tsinghua University Beijing 100084China Management and Department of Energy and Resources Engineering College of EngineeringPeking UniversityBeijing 100871China

Global navigation satellite system(GNSS)carrier phase observations are two orders of higher accuracy than pseudo-range observations,and they are less affected by multipath *** a result,the time transfer accuracy can reach 0.1 ns,and the frequency transfer stability can reach 1×10^-15 with carrier phase(CP)method,therefore CP method is considered the most accurate and promising time transfer *** focus of this paper is to present a comprehensive summary of CP method,with specific attention directed toward day-boundary clock jump,ambiguity resolution(AR),multi-system time transfer and real-time time ***-boundary clock jump is essentially caused by pseudo-range *** approaches were proposed to solve the problem,such as continuously processing strategy,sliding batch and bidirectional filtering methods which were compared in this ***,researches on AR in CP method were *** scholars attempted to fix the single-difference ambiguities to improve the time transfer result,however,owing to the uncalibrated phase delay(UPD)was not considered,the current studies on AR in CP method were still ***,because four GNSS systems could be used for time-transfer currently,which was helpful to increase the accuracy and reliability,the researches on multi-system time transfer were ***’s more,real-time time transfer attracted more attention nowadays,the preliminary research results were presented.

关键词： carrier phase(CP) time transfer day-boundary clock jump ambiguity resolution(AR) multi-system time transfer real-time time transfer

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A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot

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Frontiers of Information Technology & Electronic engineering 2022年第8期23卷 1217-1228页

作者： Manjun TIAN Xiali LI Shihan KONG Licheng WU Junzhi YU First Research Institute of the Ministry of Public Security of PRC Beijing 100048China School of Information Engineering Minzu University of ChinaBeijing 100081China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

To tackle the problem of aquatic environment pollution,a vision-based autonomous underwater garbage cleaning robot has been developed in our *** propose a garbage detection method based on a modified YOLOv4,allowing high-speed and high-precision object ***,the YOLOv4 algorithm is chosen as a basic neural network framework to perform object *** the purpose of further improvement on the detection accuracy,YOLOv4 is transformed into a four-scale detection *** improve the detection speed,model pruning is applied to the new *** virtue of the improved detection methods,the robot can collect garbage *** detection speed is up to 66.67 frames/s with a mean average precision(mAP)of 95.099%,and experimental results demonstrate that both the detection speed and the accuracy of the improved YOLOv4 are excellent.

关键词： Object detection Aquatic environment Garbage cleaning robot Modified YOLOv4

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Development of a prototype of an intelligent system for predicting the quality of dairy manufacture

Development of a prototype of an intelligent system for pred...

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International IEEE Conference on Intelligent systems, IS

作者： Yaroslav Smitiukh Yuliia Samoilenko Yuliia Kostiuk Olena Kryvoruchko Kateryna Stepashkina department of automation and computer technologies of control systems National University of Food Technologies Kyiv Ukraine department of software engineering and cyber security State University of Trade and Economics Kyiv Ukraine

ISBN: (纸本)9781665492768

The technological process of the churning process in continuous butter manufacture were considered. The qualitative indicator of the water content of butter was modeled on the basis of a set of industrial data using an artificial neural network (ANN). The prototype of an intelligent system for predicting of the water content of butter allows to increase the information support of the operator-technologist. The proposed model predicts the water content of butter with an error of less than 2%. The input variables of the forecast model prototype are cream fat content, cream ripening temperature, cream supply temperature, frequency of revolutions of the stirrer of the whipping device, and consumption of the normalizing component. Further research is aimed at the development of a decision support information system for dairy manufacture and should be integrated into the subsystem of automated control of the technological process to ensure proper functioning in real time.

关键词： Productivity Dairy products Simulation Prototypes Process control Artificial neural networks Predictive models

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NeRF in Robotics: A Survey

arXiv

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arXiv 2024年

作者： Wang, Guangming Pan, Lei Peng, Songyou Liu, Shaohui Xu, Chenfeng Miao, Yanzi Zhan, Wei Tomizuka, Masayoshi Pollefeys, Marc Wang, Hesheng The University of Cambridge ETH Zurich Switzerland The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China ETH Zurich Zurich Switzerland Mechanical Systems Control Laboratory University of California Berkeley United States

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable numerous capabilities. Among these, the Neural Radiance Field (NeRF) has sparked a trend because of the huge representational advantages, such as simplified mathematical models, compact environment storage, and continuous scene representations. Apart from computer vision, NeRF has also shown tremendous potential in the field of robotics. Thus, we create this survey to provide a comprehensive understanding of NeRF in the field of robotics. By exploring the advantages and limitations of NeRF, as well as its current applications and future potential, we hope to shed light on this promising area of research. Our survey is divided into two main sections: The Application of NeRF in Robotics and The Advance of NeRF in Robotics, from the perspective of how NeRF enters the field of robotics. In the first section, we introduce and analyze some works that have been or could be used in the field of robotics from the perception and interaction perspectives. In the second section, we show some works related to improving NeRF's own properties, which are essential for deploying NeRF in the field of robotics. In the discussion section of the review, we summarize the existing challenges and provide some valuable future research directions for reference. © 2024, CC BY-NC-ND.

关键词： Robotics

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Development of a UAV-based System for Technical Diagnostics of Overhead Power Lines

Development of a UAV-based System for Technical Diagnostics ...

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International Conference on Computational Problems of Electrical engineering (CPEE)

作者： Oleksandr Kozlovskyi Dmitro Trushakov Serhiy Rendzinyak Vasyl Korud Department of Electrical Systems and Energy Management Central Ukrainian National Technical University Kropyvnytskyi Ukraine Department of Automation and Control in Technical Systems Central Ukrainian National Technical University Kropyvnytskyi Ukraine Faculty of Electronics and Computer Technologies Ivan Franko National University of Lviv Lviv Ukraine Institute of Power Engineering and Control System Lviv Polytechnic National University Lviv Ukraine

The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics of overhead lines based on UAVs was developed, for which the necessary diagnostic parameters were selected according to informative criteria. An analysis of types of UAVs was carried out in order to determine their suitability and efficiency of use for diagnosing the condition of overhead lines.

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Optimization of Robot End-Effector Load Gravity Compensation for Unmanned Live Work in Electric Power Distribution Networks Based on Improved PSO Algorithm

Optimization of Robot End-Effector Load Gravity Compensation...

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2023 China automation Congress, CAC 2023

作者： Chen, Jinge Chen, Xin Hu, Chenyu Huang, Guangxian Sun, Shu Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering-Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Xianning Power Supply Company Distribution Department Xianning437000 China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Equipment Technology Center Wuhan430077 China

ISBN: (纸本)9798350303759

In the field of electric power distribution network operation, most tasks involve contact operations. A key technology to enable the flexible operation of robots in live distribution network tasks is the installation of six-dimensional force sensors on the robot's end flange. These sensors allow the robot to perceive external environmental contact forces. However, the presence of the end load interferes with the accurate perception of external forces. Aiming at the gravity compensation of robot end load, an optimization algorithm of gravity compensation based on particle swarm optimization is proposed. In this method, the optimal solution model is established with the objective of minimum sum of squared errors, and the particle swarm optimization algorithm is used to estimate the mounting declination angle of the force sensor and improve the precision of gravity compensation. The experiments show that the proposed method can effectively reduce the maximum gravity compensation error and the average gravity compensation error in each direction after optimization, in which the maximum gravity compensation error of the resultant force is reduced by 9.11% and the average gravity compensation error of the resultant force is reduced by 12.34%. © 2023 IEEE.

关键词： Error compensation

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Robust Data-Driven control Against Actuator FDI for Unknown Linear systems

Robust Data-Driven Control Against Actuator FDI for Unknown ...

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International Conference on control and automation (ICCA)

作者： Wenjie Liu Jian Sun Fang Deng Gang Wang Jie Chen National Key Lab of Autonomous Intelligent Unmanned Systems School of Automation Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Department of Control Science and Engineering Tongji University Shanghai China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper designs a data-driven controller for unknown linear systems whose actuators suffer from false data injection (FDI) attacks, using only noisy input-state data. To achieve this objective, a general FDI attack model is introduced, which imposes constraints only on the switching frequency of attack channels and the magnitude of attack matrices. A time-varying state feedback control law is designed based on offline and online input-state data, which adapts to the channel switching of FDI attacks. This is achieved by solving a data-based semi-definite programs (SDPs) on-the-fly such that stabilizing the set of subsystems consistent with both offline clean data and online attack-corrupted data. It is shown that under mild conditions on the attack and the noise, the feasibility of the proposed SDP guarantees that the controller stabilizes the attack-corrupted system. A numerical example is presented to validate the effectiveness of the proposed method.

关键词： Linear systems Switched systems Actuators State feedback Switching frequency Switches control systems

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Discretizing Continuous Action Space with Unimodal Probability Distributions for On-Policy Reinforcement Learning

arXiv

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arXiv 2024年

作者： Zhu, Yuanyang Wang, Zhi Zhu, Yuanheng Chen, Chunlin Zhao, Dongbin The Department of Control Science and Intelligent Engineering School of Management and Engineering Nanjing University Nanjing210093 China The Research Center for Novel Technology of Intelligent Equipment Nanjing University Nanjing210093 China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

For on-policy reinforcement learning, discretizing action space for continuous control can easily express multiple modes and is straightforward to optimize. However, without considering the inherent ordering between the discrete atomic actions, the explosion in the number of discrete actions can possess undesired properties and induce a higher variance for the policy gradient estimator. In this paper, we introduce a straightforward architecture that addresses this issue by constraining the discrete policy to be unimodal using Poisson probability distributions. This unimodal architecture can better leverage the continuity in the underlying continuous action space using explicit unimodal probability distributions. We conduct extensive experiments to show that the discrete policy with the unimodal probability distribution provides significantly faster convergence and higher performance for on-policy reinforcement learning algorithms in challenging control tasks, especially in highly complex tasks such as Humanoid. We provide theoretical analysis on the variance of the policy gradient estimator, which suggests that our attentively designed unimodal discrete policy can retain a lower variance and yield a stable learning process. © 2024, CC BY.

关键词： Contrastive Learning

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Short - Term Prediction of Coke Pushing Current Peak Based on Improved ARIMA Model

Short - Term Prediction of Coke Pushing Current Peak Based o...

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Industrial Cyber-Physical systems (ICPS)

作者： Haiyang Wei Luefeng Chen Jie Hu Yi Ren Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Tokyo Institute of Technology Yokohama Japan

Coke pushing current is an indicator to evaluate the difficulty of coke pushing operation. The higher coke pushing current is, the greater coke pushing resistance is, and the more difficult coke is to push out. Accurate prediction of current peak during future coke pushing operation can provide more time for production personnel to adjust production status and avoid difficult coke pushing in carbonization chamber. In this paper, a combination prediction model based on VMD (Variational Mode Decomposition) and improved ARIMA (Autoregressive Integrated Moving Average) models is proposed. Firstly, VMD algorithm is used to decompose time series of coke pushing current peak, de-noising data, and extracting main information of time series. Then, ARIMA model is used to predict mean change of linear elasticity and GARCH (Generalized Autore-gressive Conditional Heteroskedasticity) model is introduced to predict ARIMA model residual and improve heteroscedasticity of nonlinear part of time series, and then ARIMA-GARCH model is established. Finally, predicted value is obtained by the sum of each component prediction. The experimental results show that the proposed prediction model has a high prediction accuracy in the short-term prediction of coke pushing current peak. The scheme is applied to actual coking production to guide production of coke.

关键词： Resistance Ovens Time series analysis Noise reduction Production Predictive models Prediction algorithms

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Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays

Stability and Bifurcation control of Fractional BAM Neural N...

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Chinese control Conference (CCC)

作者： Feng Liu Wei Wang Gang Cai Feifan Zhou Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

Based on fractional calculus theory and reaction-diffusion equation theory, a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is investigated. By constructing the phase space basis based on the Laplace operator eigenvector, the system equation is linearized to obtain the characteristic equation. Then, the characteristic equation is analyzed, and the local stability of the system at the equilibrium point is discussed. And taking the time delay as the bifurcation parameter, the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay changes. Moreover, a state feedback controller is designed to control the bifurcation of the system. Finally, the theoretical derivation is verified by numerical simulation.

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