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第40届中国控制会议

作者： Zhexin Shi Jianglong Yu Jiahong Wei Xiwang Dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University) Ministry of Education of ChinaChongqing University

The cooperative guidance design and analysis issues for multiple robots system are investigated. First, a cooperative guidance structure is constructed by leader layer robots and follower layer robots. Then, for the leader robot layer, the cooperative detection guidance law is designed to achieve the coordination of the detection field of view（FOV）, while providing the reference trajectories. Third, for the follower robot layer, the time-varying line of sight（LOS） angle formation tracking guidance law is proposed based on the leader robots’ LOS angle trajectories convex combination. In addition, the design process is given ***, a cooperative guidance platform consisting of two leaders, three followers, and a target is constructed. The theoretical results are verified by numerical simulation examples, and experimental results are presented on the platform.

关键词： Paper Instruction Chinese control Conference

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Singularity representation and workspace determination of the parrallel robot PAR4

Singularity representation and workspace determination of th...

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International Conference on Sciences and Techniques of Automatic control and Computer engineering (STA)

作者： Ahlem Saidi Neila Mezghani Ben Romdhane Laboratory of sciences and technique of automatic control and computing (Lab-STA) Nationnal school of engineering of sfax Sfax Tunisia

ISBN: (数字)9781728188157

ISBN: (纸本)9781728188164

In this paper, the Singularity representation and workspace determination of the parrallel robot PAR4 are presented. The serial singularity (type 1) is determined using the kinematic matrix. This type of singularity indicates the unreachable points in the workspace. Based on the inverse geomatric model (MGI) of the parallel robot PAR4 the workspace is determined. Numerical results are presented showing some singularity of type 1 and their representation of the robot PAR4. Also, the workspace of this robot is presented.

关键词： Parallel robots Geomagnetism Simulation Computational modeling Kinematics Numerical models

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Tribological behaviour diagnostic and fault detection of mechanical seals based on acoustic emission measurements

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Friction 2019年第6期7卷 572-586页

作者： Hossein TOWSYFYAN Fengshou GU Andrew D BALL Bo LIANG Institute of Sound and Vibration Research(ISVR) Digital Signal Processing and Control GroupUniversity of SouthamptonSouthampton SO171BJUK School of Computing and Engineering University of HuddersfieldHuddersfield HD13DHUK

Acoustic emission(AE) has been studied for monitoring the condition of mechanical seals by many researchers, however to the best knowledge of the authors, typical fault cases and their effects on tribological behaviour of mechanical seals have not yet been successfully investigated. In this paper, AE signatures from common faults of mechanical seals are studied in association with tribological behaviour of sealing gap to develop more reliable condition monitoring approaches. A purpose-built test rig was employed for recording AE signals from the mechanical seals under healthy and faulty conditions. The collected data was then processed using time domain and frequency domain analysis methods. The study has shown that AE signal parameters: root mean squared(RMS) along with AE spectrum, allows fault conditions including dry running, spring out and defective seal faces to be diagnosed under a wide range of operating conditions. However, when mechanical seals operate around their transition point, conventional signal processing methods may not allow a clear separation of the fault conditions from the healthy baseline. Therefore an auto-regressive(AR) model has been developed on recorded AE signals to classify different fault conditions of mechanical seals and satisfactory results have been perceived.

关键词： tribology acoustic emission condition monitoring

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Reconfigurable Intelligent Surface Enhanced Wireless Localization: Phase Optimization for Malicious Interference Mitigation

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IEEE Transactions on Communications 2025年

作者： Zhang, Yi Xie, Yajing Wang, Lijia Liwang, Minghui Wang, Xianbin Xiamen University Ministry of Education of China Department of Information and Communication Engineering Key Laboratory of Multimedia Trusted Perception and Efficient Computing Xiamen China Tongji University Shanghai Research Institute for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai China Western University Department of Electrical and Computer Engineering ON Canada

Recently, unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) have merged as important enabling technologies for localization coverage extension and localization accuracy improvement under signal blockage and malicious interference conditions. However, most existing works assume known locations of jammers, which is generally impractical in real-world networks. To overcome this challenge, we propose a novel RIS-enhanced wireless localization framework against malicious interference with the support of either narrowband or orthogonal frequency division multiplexing (OFDM) pilot signals. A two-stage anti-jamming localization approach is developed to first estimate the unknown channel and signal information of the jammer and then localize the user’s position by eliminating the jamming signal. More importantly, we utilize the full potential of RIS to improve localization accuracy by optimizing the phase shift profile during the iterative process. Extensive simulation results demonstrate the commendable performance of our proposed framework, which can not only mitigate the jamming effect but also achieve better localization accuracy, offering a good reference for future heterogeneous and complex wireless networks. © 1972-2012 IEEE.

关键词： Frequency division multiplexing

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Artificial intelligence in cancer target identification and drug discovery

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Signal Transduction and Targeted Therapy 2022年第6期7卷 1951-1974页

作者： Yujie You Xin Lai Yi Pan Huiru Zheng Julio Vera Suran Liu Senyi Deng Le Zhang College of Computer Science Sichuan UniversityChengdu 610065China Laboratory of Systems Tumor Immunology Friedrich-Alexander-Universität Erlangen-Nürnberg(FAU)and Universitätsklinikum ErlangenErlangen 91052Germany Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesRoom D5131068 Xueyuan AvenueShenzhen University TownShenzhen 518055China School of Computing Ulster UniversityBelfast BT151EDUK Institute of Thoracic Oncology Department of Thoracic SurgeryWest China HospitalSichuan UniversityChengdu 610065China Key Laboratory of Systems Biology Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhou 310024China Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as ***,we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover ***,we describe the scope of artificial intelligence biology analysis for novel anticancer target ***,we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence ***,we showcase the applications of artificial intelligence approaches in cancer target identification and drug *** together,the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer,thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.

关键词： drugs cancer drug

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In-Situ 3D Printing Monitoring in Dynamic Environments via Self-Supervised Deep Neural Network Adaptation

In-Situ 3D Printing Monitoring in Dynamic Environments via S...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Fang Wang Gang Xiong Qihang Fang Zhen Shen Di Wang Li Wan Xisong Dong Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Mechanical and Automotive Engineering South China University of Technology Guangzhou China Beijing Ten Dimensions Technology Co. Ltd. Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

3D printing technology has rapidly advanced, yet the variability in deployment environments poses significant challenges for monitoring systems, because the dynamic deployment environments such as changes in lighting and monitoring camera status, can severely impact the effectiveness and robustness of monitoring systems. To tackle this problem in monitoring system, this paper introduces a novel approach for deep neural network (DNN) adaptation to the dynamic environments through self-supervised learning and applies it to during in-situ monitoring. Specifically, we introduce a self-supervised learning strategy that leverages the auxiliary reconstruction task during in-situ monitoring, subsequently applying self-supervised fine-tuning to classification tasks with a new imbalanced-aware classification loss. Our methodology was rigorously evaluated using a real-world dataset for 3D printing defect detection. The experimental outcomes affirm the robustness of our approach, showcasing a higher defect detection accuracy rate than baselines. This substantially mitigates the adverse effects associated with printing defects, thereby increasing the reliability and quality of 3D printing processes.

关键词： Adaptation models Lighting Artificial neural networks Self-supervised learning Three-dimensional printing Feature extraction Robustness Monitoring Image reconstruction Defect detection

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Path Planning of Mobile Robot Based on an Improved Genetic Algorithm

Path Planning of Mobile Robot Based on an Improved Genetic A...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zenghua Chen Gang Xiong Sheng Liu Zhen Shen Yue Li State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Automobile Chang'an University Xi'an China

ISBN: (数字)9781665492270

ISBN: (纸本)9781665492287

In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations; Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm; Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles; Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning.

关键词： Sociology Clustering algorithms Path planning Planning Trajectory Statistics Collision avoidance

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Short-Term and Mid-Term Population Projections Especially of Germany via WASD Neural Network: Theoretical Parts

Short-Term and Mid-Term Population Projections Especially of...

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第40届中国控制会议

作者： Zhiwen Yuan Siyuan Feng Chengxu Ye Yunong Zhang School of Computer Science and Engineering Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education School of Computer Science Qinghai Normal University

Population has a direct impact on the demands of consumption, resource, and employment. Population factors, such as size and growth rate, are crucial in making decisions and plans of trade, environment protection, resource allocation and human resource development. Thus, population projection is an essential part of strategy development for companies as well as governments, and draws the attention of many researchers. Some projection methods have been developed, but most of the popular ones require a vast knowledge in demography and only can be operated by skilled professionals. In this paper, as an improvement, we theoretically develop a regression model and a subtrend model of WASD（weights and structure determination）neural network in a simultaneous manner to make population projections especially of Germany in the mid term and near ***, we aim at utilizing the learning capabilities of the WASD neural-network models with single input and multiple inputs, having been very popular recently, to propose these easy-used and high accuracy models for verifications and projections via later computer experiments.

关键词： Germany population Projections Neural network WASD（weights and structure determination） Multiple inputs

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Transverse momentum spectra and angular correlations in -hadron production in relativistic heavy-ion collisions

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The European Physical Journal Plus 2025年第1期140卷 1-20页

作者： Gao, Zhan Chen, Lin Hu, Peng-Hui Xie, Man Zhang, Han-Zhong Key Laboratory of Quark and Lepton Physics (MOE) and Institute of Particle Physics Central China Normal University Wuhan China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China University of Science and Technology of China Hefei People’s Republic of China Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum Matter South China Normal University Guangzhou China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear Science Southern Nuclear Science Computing Center South China Normal University Guangzhou China

We carry out a detailed study of medium modifications on transverse momentum spectra and angular correlations between a large transverse momentum hadron and a $$Z/\gamma$$ trigger in relativistic heavy-ion collisions within a perturbative QCD parton model improved by the Sudakov resummation technique. The total energy loss of a hard parton propagating inside the medium is employed to modify the fragmentation function, while the medium-induced transverse momentum broadening is included in the resummation approach, and both of them are related to the jet transport parameter and obtained by the higher-twist formalism. We obtain good agreements with the existing data on transverse momentum and azimuthal angular correlations for the $$Z/\gamma$$ -hadron pairs in pp and AA collisions and predict the correlations for the $$\gamma$$ -hadron in central PbPb collisions at 5.02 TeV. The numerical analyses for the $$Z/\gamma$$ -hadron in central PbPb collisions show that the normalized angular distribution is decorrelated due to the medium-induced transverse momentum broadening; however, the angular correlation is enhanced due to the parton energy loss, namely anti-broadening. The observed modification of the angular correlation is a result of the competition between the broadening and the anti-broadening. This work provides a reliable theoretical tool for a comprehensive and precise study of jet quenching in relativistic heavy-ion collisions.

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Synthesis of the Decision Support System for controlling the Process of Combined Destruction of Butyl Rubber Vulcanizates 3

Synthesis of the Decision Support System for Controlling the...

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3rd International Conference on control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Tikhomirov, German Karmanov, Andrey Zhatova, Victoria Popov, Alexey Obraztsov, Nikolay Podvalny, Evgeniy Voronezh State University Department of System Analysis and Management Voronezh Russia Voronezh State Technical University Department of Automated and Computing Systems Voronezh Russia Voronezh State University Department of Geoecology of Environmental Monitoring Voronezh Russia Voronezh State University of Engineering Technologies Department of Information and Control Systems Voronezh Russia Russian Presidental Academy of National Economy and Public Administration Department of Mathematics and Information Technologies in Management Moscow Russia

ISBN: (纸本)9781665439817

the article is devoted to solving the problems of synthesis of algorithmic support of the decision support system for the controlled destruction of resin vulcanizates of butyl rubber. As an object of research, the destruction processes have been selected, which are carried out by combining external destructive factors: ionization irradiation and subsequent thermomechanical treatment. Based on the results of the system analysis of the destruction process stages as control objects, the main and cross system connections between the input, internal parameters of the process and the physical properties of the final product have been revealed. The most preferred channels for controlling the rate of physical and chemical processes occurring during destruction have been selected. Using a combination of control actions, a method and an algorithm for controlling the stages of destruction has been proposed, which allows for programmed control of the operating parameters of the process to obtain reclaimed butyl rubber with target quality indicators. The structural synthesis of the mathematical support of the decision support system, which calculates the optimal values of the process parameters in accordance with the formed search criteria, has been carried out. An algorithm for controlling the destruction process has been developed, which calculates the optimal parameters of the process using the mathematical tools, which includes the Choquet integral, the Sugeno fuzzy measure, and a genetic algorithm for solving optimization problems. © 2021 IEEE.

关键词： Irradiation

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