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Chat with ChatGPT on Industry 5.0:Learning and Decision-Making for intelligent Industries

IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 831-834页

作者： Fei-Yue Wang Jing Yang Xingxia Wang Juanjuan Li Qing-Long Han State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia

THE current ChatGPT phenomenon has signaled a new era of Artificial Intelligence moving from Algorithmic Intelligence to Linguistic Intelligence where interactive activities between actual and artificial,real and virtual,human and machine play an active and important role online and in *** IEEE/CAA JAS,we are interested in investigating the impact and significance of this new era on industrial development,especially control and automation for manufacturing and production.

关键词： GPT artificial automation

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Oscillation Trajectory Optimization and Control Method for Two-Link Underactuated Manipulators 42

Oscillation Trajectory Optimization and Control Method for T...

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42nd Chinese Control Conference, CCC 2023

作者： Wang, Lejun Wang, Huiming Tang, Xianlun Huang, Zixin Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China

ISBN: (纸本)9789887581543

This paper provides an oscillation trajectory optimization and control method for two-link underactuated manipulators (UMs) in a vertical plane. The proposed method solves the problem that the UMs cannot always enter the balance region in the partitioning method. First, we establish the system dynamic model, and analyze the system couple characteristics. Then, we program an oscillation trajectory for the active link, and use the intelligent method to obtain the trajectory parameters, so ensuring the system can reach the area adjacent to the target position through tracking control. Next, we design the controller to realize the stable control at the target position. Finally, the simulation results show the effectiveness and generality of the control strategy. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Trajectories

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Development of a Universal RNA Dual-Terminal Labeling Method for Sensing RNA-Ligand Interactions

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CCS Chemistry 2023年第1期5卷 221-233页

作者： Longhuai Cheng Dejun Ma Jie Zhang Xueying Kang Yang Wu Yi Zhao Long Yi Zhen Xi State Key Laboratory of Elemento-Organic Chemistry Department of Chemical BiologyCollege of ChemistryNational Pesticide Engineering Research CenterCollaborative Innovation Center of Chemical Science and EngineeringNankai UniversityTianjin 300071 State Key Laboratory of Organic-Inorganic Composites and Beijing Key Laboratory of Bioprocess Beijing University of Chemical Technology(BUCT)Beijing 100029 Key Laboratory of Intelligent Information Processing Research Center for Ubiquitous Computing SystemsInstitute of Computing TechnologyChinese Academy of SciencesBeijing 100190

Dual labeling of an RNA can provide Förster resonance energy transfer(FRET)sensors for studying RNA folding,miRNA maturation,and RNA-protein ***,we report the development of a highly efficient strategy for direct dual-terminal labeling of any RNA of *** explored new Michael cycloaddition for facile labeling of 5′-terminal RNA with improved *** chemical tetrazinylation of RNA at the 3′-terminus was achieved with the highly efficient and catalysis-free tetrazine-cycloalkyne *** single-terminal labeling methods were combined for dual-terminal labeling of an RNA including short hairpin RNA,pre-miRNA,riboswitch,and noncoding ***,these dual-labeled RNA-based FRET sensors were used to monitor RNA-ligand interactions in vitro and in live *** is anticipated that these universal RNA labeling strategies will be useful to study RNA structures and functions.

关键词： dual labeling Förster resonance energy transfer sensor Michael cycloaddition tetrazinecycloalkyne ligation RNA-ligand interaction

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Unveiling Dynamic System Strategies for Multisensory Processing: From Neuronal Fixed-Criterion Integration to Population Bayesian Inference

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Research 2023年第2期2022卷 81-100页

作者： Jiawei Zhang Yong Gu Aihua Chen Yuguo Yu State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Shanghai Artificial Intelligence LaboratoryResearch Institute of Intelligent and Complex Systems and Institute of Science and Technology for Brain-Inspired IntelligenceHuman Phenome InstituteShanghai 200433China Key Laboratory of Primate Neurobiology Institute of NeuroscienceCAS Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghaiChina Key Laboratory of Brain Functional Genomics(Ministry of Education) East China Normal University3663 Zhongshan Road N.Shanghai 200062China

Multisensory processing is of vital importance for survival in the external *** circuits can both integrate and separate visual and vestibular senses to infer self-motion and the motion of other ***,it is largely debated how multisensory brain regions process such multisensory information and whether they follow the Bayesian strategy in this process.

关键词： Integration Fixed Criterion

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Data-Driven Discovery of Nonlinear Dynamical systems from Noisy and Sparse Observations

Data-Driven Discovery of Nonlinear Dynamical Systems from No...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Zhu, Wei Pei, Chao Liang, Yulan Chen, Zhang Li, Jingsui School of Science Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing China College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9798331517021

Sparse Identification of Nonlinear Dynamics (SINDy) is a data-driven algorithm for interpretability mod-eling. SINDy has a strong ability to learn dynamical systems from time series data. Sparse Identification of Nonlinear Dynamics (SINDy) can extract equations from data, but its performance will degrade when data has noise or sparse. In order to deal with this case, the idea of Monte Carlo Markov Chain (MCMC) is introduced, which is used to optimally select models. The SINDy with MCMC (MCMC-SINDy) can comprehensively discover model structures by employing random samples in data space. Simulation results show that MCMC-SINDy is more robust than SINDy with 1 % -15 % levels of noise or sparse 0.5. These results are promising for the discovery of governing equations for complex systems in neuroscience, power grids, epidemiology, finance or ecology, where governing equations have remained elusive. mportantly, compared to existing machine learning methods, the accuracy of modeling using MCMC SINDy is higher. © 2024 IEEE.

关键词： Markov chains

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Tightly-coupled Lidar-GNSS-Inertial Fusion Odometry and Mapping

Tightly-coupled Lidar-GNSS-Inertial Fusion Odometry and Mapp...

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第43届中国控制会议

作者： Shuwei Yu Jing Li Tianwei Niu Junzheng Wang Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper proposes a tightly-coupled lidar-GNSS-inertial fusion system that achieves accurate state estimation and mapping for robot *** system effectively fuses lidar points,GNSS measurements,and IMU data using the iterated error state Kalman filter algorithm to obtain precise,drift-free,and real-time *** optimize computational efficiency,an incremental tree structure,ikdtree,is employed for managing a local map,and different Kalman gain formulas are utilized to process GNSS and lidar point observations separately to lower the computation ***,a factor graph is introduced to optimize the pose *** selectively introducing keyframes based on the odometry estimation,the graph incorporates odometry,GNSS measurements,and loop closure constraints to optimize all keyframe poses,resulting in a precise trajectory and global ***,extensive experiments are conducted using the KITTI dataset and several real-world scenarios to validate the proposed *** experimental results demonstrate that our method achieves precise localization and mapping across diverse environments.

关键词： State estimation Mapping Sensor fusion Robot navigation

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Interpretable Fourier Neural Ordinary Differential Equations

Interpretable Fourier Neural Ordinary Differential Equations

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Hanlin Bian Wei Zhu Zhang Chen Jingsui Li Chao Pei Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

Numerous interacting elements can form complex systems. However, describing complex systems is extremely challenging and lacks interpretability. The construction of models still heavily relies on scientists’ understanding of complex systems. This paper explores the use of neural ordinary differential equations in the field of complex system modeling. The proposed Fourier neural ordinary differential equations offer interpretability and a relatively simple structure. By building upon interpretable modeling, the scale is significantly reduced. It is possible to deduce the system’s expression from the model’s parameters. Finally, a real-world system is provided to illustrate the effectiveness of the proposed model, demonstrating its commendable robustness.

关键词： Training Atmospheric modeling Fitting Time series analysis Ordinary differential equations Predictive models Mathematical models

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Design and application of intelligent monitoring system for geological hazards 41

Design and application of intelligent monitoring system for ...

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第41届中国控制会议

作者： Yutong Pan Chengda Lu Wanke Yu Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development and utilization of natural resources,geological hazards have posed a great threat to people's life and property *** is of great significance to realize the design of distributed geological disaster monitoring experimental system aimed at a series of problems,such as ecological environmental damage and major natural ***,this paper conducts the system requirements analysis based on the Three Gorges area as an ***,the system architecture and function is designed,and the system hardware configuration and application software design are carried ***,geological hazards intelligent monitoring system is developed and has been verified in Zigui-Badong region of the Three Gorges,which can effectively improve the information utilization rate and monitoring efficiency in the process of geological hazards *** results show that the system works well and can effectively monitor the occurrence of geolo gical hazards.

关键词： Geological hazards system design hardware configuration application software the Three Gorges

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Adaptive Neural Tracking Control for Nonlinear Servo System with Unknown Time-Varying Parameters and Uncertainties 42

Adaptive Neural Tracking Control for Nonlinear Servo System ...

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42nd Chinese Control Conference, CCC 2023

作者： Zhang, Faxiang Gao, Guanbin Na, Jing Wu, Jiande Kunming University of Science and Technology Faculty of Mechanical and Electrical Engineering Yunnan International Joint Laboratory of Intelligent Control and Application of Advanced Equipment Kunming650500 China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Kunming650500 China

ISBN: (纸本)9789887581543

This paper solves the neural network (NN) tracking control problem for uncertain nonlinear servo system with time-varying parameters and uncertainties. To address the uncertain nonlinear function with unknown time-varying parameters (i.e., unknown nonlinear spatiotemporal function), the time-varying parameter extraction method is used to separate the time-varying parameters from uncertain nonlinear spatiotemporal function, which yields an unknown state-based boundary function. By the tools of NN and adaptive technology, an adaptive neural tracking controller is designed, which guarantees the uniformly ultimately bounded (UUB) performance of the resulting closed-loop system. The effectiveness of the designed method is verified by simulations. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Servomechanisms

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Prediction Method of Blast Furnace Fuel Ratio Based on Spectral Clustering and Extreme Learning Machine Model 41

Prediction Method of Blast Furnace Fuel Ratio Based on Spect...

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第41届中国控制会议

作者： Jingjie Liang Yan Yuan Shuqiao Wang Zhuofu Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The blast furnace fuel ratio,as the main index reflecting the blast furnace fuel consumption,plays an important role in guiding blast furnace *** order to solve the problem of insufficient stability of the existing fuel ratio prediction model under the condition of process parameters fluctuation,a prediction method of blast furnace fuel ratio based on spectral clustering and extreme learning machine model is ***,on the basis of analyzing the influencing factors of fuel ratio,the classification results after clustering are visualized with t-SNE dimension reduction downscaling and spectral clustering method;Secondly,for the classification results after clustering,the extreme learning machine is used to establish the sub-models,and the PSO algorithm was used to optimize the input weights of hidden layer and the bias of hidden layer *** results show that the proposed method has high prediction accuracy.

关键词： Fuel Ratio Spectral Clustering Extreme Learning Machine(ELM) t-SNE Particle Swarm Optimization(PSO)

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