检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Li, Juanjuan Li, Junqing Wang, Xiao Qin, Rui Yuan, Yong Wang, Fei-Yue The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Qingdao Academy of Intelligent Industries Qingdao266109 China School of Mathematics Renmin University of China Beijing100872 China Macao Institute of Systems Engineering Macau University of Science and Technology 999078 China

Aiming to deal with the challenge of data security and data pricing in data trading markets, we propose the novel multi-blockchain-based framework and design the related pricing mechanisms. Specifically, data recording and trading are conducted separately in the Data Blockchain (DChain) and the Value Blockchain (VChain). Based on these blockchains, two-layer data trading markets are established to manage the initial data trading in the primary market and the data resale in the secondary market. Pricing mechanisms are proposed to protect the formulated data trading markets against strategic trading behaviors and balance the payoffs of both suppliers and users. In the regular data trading on VChain-S2D, two auction models are used to deal with users' strategic bidding in terms of the demand scale, where the incentive-compatible Vickrey-Clarke-Groves (VCG) model is dedicated to the low-demand trading scenario, while the nearly incentive-compatible Monopolistic Price (MP) model is for the high-demand trading scenario. In the temporary data trading on VChain-D2S, a reverse auction mechanism named Two-Stage Obscure Selection (TSOS) is designed to regulate both suppliers' quoting and users' valuation strategies. Moreover, experiments are carried out to validate our theoretical analysis. Our work is expected to enhance the data security and improve the trading efficiency. © 2022, The Authors. All rights reserved.

关键词： Blockchain

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Dynamical causality under invisible confounders

arXiv

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arXiv 2024年

作者： Yan, Jinling Zhang, Shao-Wu Zhang, Chihao Huang, Weitian Shi, Jifan Chen, Luonan MOE Key Laboratory of Information Fusion Technology School of Automation Northwestern Polytechnical University Xi’an710072 China Key Laboratory of Systems Biology Shanghai Institute of Biochemistry and Cell Biology Center for Excellence in Molecular Cell Science Chinese Academy of Sciences Shanghai200031 China NCMIS CEMS RCSDS Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematics Sciences University of Chinese Academy of Sciences Beijing100049 China School of Computer Science and Engineering South China University of Technology Guangdong Guangzhou510006 China Guangdong Institute of Intelligence Science and Technology Hengqin Guangdong Zhuhai519031 China Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China State Key Laboratory of Medical Neurobiology MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University Shanghai200032 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Key Laboratory of Systems Health Science of Zhejiang Province School of Life Science Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Chinese Academy of Sciences Hangzhou310024 China

Causality inference is prone to spurious causal interactions, due to the substantial confounders in a complex system. While many existing methods based on the statistical methods or dynamical methods attempt to address misidentification challenges, there remains a notable lack of effective methods to infer causality, in particular in the presence of invisible/unobservable confounders. As a result, accurately inferring causation with invisible confounders remains a largely unexplored and outstanding issue in data science and AI fields. In this work, we propose a method to overcome such challenges to infer dynamical causality under invisible confounders (CIC method) and further reconstruct the invisible confounders from time-series data by developing an orthogonal decomposition theorem in a delay embedding space. The core of our CIC method lies in its ability to decompose the observed variables not in their original space but in their delay embedding space into the common and private subspaces respectively, thereby quantifying causality between those variables both theoretically and computationally. This theoretical foundation ensures the causal detection for any high-dimensional system even with only two observed variables under many invisible confounders, which is actually a long-standing problem in the field. In addition to the invisible confounder problem, such a decomposition actually makes the intertwined variables separable in the embedding space, thus also solving the non-separability problem of causal inference. Extensive validation of the CIC method is carried out using various real datasets, and the experimental results demonstrates its effectiveness to reconstruct real biological networks even with unobserved confounders. © 2024, CC BY-NC-ND.

关键词： Time series

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control System Design for Weight on Bit in complex Geological Drilling Process

Control System Design for Weight on Bit in Complex Geologica...

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第三十八届中国控制会议

作者： Sike Ma Min Wu Jun Cheng Luefeng Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

With the increase in drilling depth, the encountered formations become more complicated, and industrial controller for weight on bit has limited precision due to the uncertain and varying formations. In this paper, we design a scheme of control system for weight on bit to achieve higher control precision in complex geological drilling process. A double-loop control structure is introduced, which involves with two system models: a multi-degree-of-freedom lumped parameter drill string model and a finite element bit-rock interaction model. The effect of varying formations on weight on bit is analyzed, and a control strategy for control system is presented in this paper.

关键词： Drilling process weight on bit control system drill string model bit-rock interaction model uncertain formations

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Stability Analysis of Nonlinear Teleoperation systems With Time-Varying Delays Via A Delay-Product-Type Functional

Stability Analysis of Nonlinear Teleoperation Systems With T...

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第三十八届中国控制会议

作者： Xiao-Hui Guo Chuan-Ke Zhang Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper is concerned with the stability analysis of a class of nonlinear teleoperation systems with time-varying delays. The proportional derivative position position control scheme with asymmetrical time-varying delays in control loops is considered for the master and the slave robots. Firstly, a new Lyapunov-Krasovskii functional（LKF） with several delayproduct-type terms is constructed by using the information of asymmetrical time-varying delays;and the Wirtinger-based integral inequality and the reciprocally convex matrix inequality are used to estimate the derivative of the LKF. As a result, a delaydependent stability criterion with less conservatism is established. Finally, an example is given to show the effectiveness and merits of the proposed criterion.

关键词： Nonlinear teleoperation system time-varying delay stability analysis linear matrix inequality

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Position Solution and Motion Simulation for Rock Drilling Arm

Position Solution and Motion Simulation for Rock Drilling Ar...

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第三十八届中国控制会议

作者： Zhilin Tang Jianqi An School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Drilling rigs are key devices in tunnel projects, which dig holes on a rock face by drilling arms. The quality and efficiency of tunnel constructions are directly determined by the positioning accuracy of the holes and time for traversing all the holes. This paper provides a complete solution for trajectory planning with accuracy and efficiency. First, this paper analyzes the structure of a drilling arm, establishes a forward kinematic model of the drilling arm by Denavit-Hartenberg convention. Next,to solve the inverse kinematics problem of drilling arm, a particle swarm optimization with adaptive inertia weight is ***, an optimal drilling sequence is found based on Hopfield network. Thereafter, a quintic polynomial method has been adopted to calculate the trajectory of the drilling arm. Finally, results of simulations show that the solution satisfies the accuracy of positioning and calculates the optimal trajectory.

关键词： inverse kinematic robot manipulator trajectory planning particle swarm optimization

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Design of Smart Home Monitoring and control System Based on Zigbee and WIFI

Design of Smart Home Monitoring and Control System Based on ...

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第三十八届中国控制会议

作者： Chentao Li Kaifeng Dong Fang Jin Junlei Song Wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Smart Home system is the use of home life associated with hardware and related application technology, the introduction of home appliance automation, remote control, intelligent processing technology in a traditional home environment, to design a provide users with comprehensive information exchange capabilities, in order to enhanced home life safety, comfort and convenience of home systems. At present, there are problems such as complicated wiring, single service, and high price in this field. In response to these problems, this paper designs a smart home system based on Zigbee and WIFI. The system consists of a terminal node, a gateway node and a remote control terminal. The terminal node and the gateway node form a home internal network through Zigbee technology, and the remote control terminal accesses and controls the home internal network through WIFI.

关键词： Smart home Zigbee WIFI Wireless transmission Remote control

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intelligent control Strategy Based on PSO-Elman Prediction Model for Ignition Temperature in Sintering Process

Intelligent Control Strategy Based on PSO-Elman Prediction M...

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第三十八届中国控制会议

作者： Yanzhuo Cen Jianqi An School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Ignition temperature in a sintering process is a dominant factor for the quality of sinter ore. However, it is difficult to control the temperature since the pressure of the gas that is used in the ignition fluctuates constantly. This paper presents an intelligent control to stabilize the ignition temperature in a sintering process. First, this paper analyzes the characteristics of an ignition process and studies the main factors affecting the ignition temperature. Then, a particle swarm optimization(PSO)-Elman model is established to predict the ignition temperature. Next, this paper describes an intelligent control system, including a fuzzy controller, two expert controllers, and a switching controller. Finally, the experimental results based on actual run data show that the intelligent control strategy stabilizes the ignition temperature.

关键词： Sintering Process Ignition Temperature PSO-Elman Prediction Model intelligent control

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Optimal tracking control for linear discrete-time stochastic system based on adaptive dynamic programming

Optimal tracking control for linear discrete-time stochastic...

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第三十八届中国控制会议

作者： Fang Wang Xin Chen Wei Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper, an adaptive dynamic programming(ADP) algorithm based on value iteration is proposed to tackle the stochastic linear quadratic(SLQ) optimal tracking control problem for discrete-time systems subject to multiplicative ***, an augmented system made up of the original system and the command generator is constructed and the condition of well-posedness for SLQ problem is given. Next, the SLQ problem is converted into the deterministic problem through system transformation. Then, ADP algorithm is utilized to solve the SLQ problem with convergence analysis. In the iteration process of ADP algorithm, the system dynamics are not essential to solve the Bellman equation but are needed to update the control gain matrix. Finally, simulation results have shown that the proposed scheme for the problem gives good tracking performance.

关键词： Stochastic system optimal tracking control adaptive dynamic programming

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Self-Adaptive PCNN Based on Maximum Entropy and its Application in Handwritten Digit Recognition

Self-Adaptive PCNN Based on Maximum Entropy and its Applicat...

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第三十八届中国控制会议

作者： Rui Zhu Wei-Hua Cao Zhe-Yi Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper mainly studies the self-adaptation of Pulse Coupled Neural Network(PCNN) and the application in handwritten digit recognition. First, the edge extraction algorithm of image using PCNN and maximum entropy is proposed, the parameters' optimization of PCNN is realized by Simple Genetic Algorithm. Then, the foveation algorithm based on PCNN is used to extract the feature points of handwritten digits. Finally, a BP neural network with two hidden layers is used to recognize the images of handwritten digits which have been preprocessed. Experimental results on handwritten digit recognition demonstrated that the proposed method reached good performance on feature extraction and the recognition has better accuracy compared with the original method using BP neural network directly.

关键词： PCNN self-adaptation foveation algorithm BP neural network

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Multi-Features Fusion Based on Boolean Map for Video Saliency Detection

Multi-Features Fusion Based on Boolean Map for Video Salienc...

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第三十八届中国控制会议

作者： Longsheng Wei Min Wang Wei Liu Xinmei Wang Jiale Sun Xu Yin School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Video saliency detection aims to extract salient objects in video. In order to resolve the problems of incomplete extraction salient area and the mixing between background and salient objects at boundary, this paper proposes a video saliency detection method via multi-features fusion based on Boolean Map. The main innovation in this method is that global topological relationship of video frames are utilized to compute saliency values. Firstly, boolean maps are generated according to the Boolean Map theory via combine motion features and color features in videos, and then attention maps are calculated by masking unsurroundedness area, finally, video saliency maps are obtained by fusing all attention maps. Experiments on Segtrack V2 and Fukuchi benchmark datesets show that the proposed method successfully obtains complete and clear boundary salient area, and it outperforms the other general models.

关键词： Video saliency detection Boolean map Multi-features fusion

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