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26th International Conference on Industrial Technology, ICIT 2025

作者： Ma, Tianyu Du, Sheng Fan, Haipeng Huang, Cheng School of Future Technology China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798331521950

Geological drilling process, owing to complex geological environment and harsh downhole conditions, generates data including characteristics such as pressure, rotational speed, and depth, which are frequently high-dimensional and noisy. These characteristics make real-time monitoring more complex. Existing methods in the geological drilling process, such as rule-based systems and threshold techniques, struggle to handle the complexity and high dimensionality of drilling data, leading to high false alarm rates and low detection accuracy. This paper develops an integrated temporal dictionary learning with isometric mapping method for monitoring geological drilling process. Specifically, Isometric Mapping is employed to perform dimensionality reduction on high-dimensional data, thereby retaining the structural features in the lower-dimensional space. Subsequently, Lasso regularization is applied for sparse coding to extract essential features from the reduced data. To address the fluctuations arising from the iterative dictionary learning process, a temporal smoothing term is incorporated to ensure the stability of the dictionary across different time steps. After that, the reconstruction errors were adopted to achieve comprehensive statistical indicators. Then the overall monitoring was realized for the plant-wide process. The effectiveness and robustness of the proposed method are demonstrated through case studies on the Tennessee-Eastman process and the actual geothermal drilling process. © 2025 IEEE.

关键词： Mapping

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A Novel Rate of Penetration Fusion Modeling Method based on Improved Dung Beetle Optimization Algorithm and Support Vector Regression

A Novel Rate of Penetration Fusion Modeling Method based on ...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Zhou, Yang Zhang, Zihan Chen, Shipeng Wu, Min Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Future Technology China University of Geosciences Wuhan430074 China

ISBN: (纸本)9798331521950

The rate of penetration (ROP) is a critical indi-cator for evaluating drilling efficiency. Developing an accurate ROP model is essential for optimizing drilling performance and addressing process control challenges. However, ROP modeling in deep geological drilling is complicated by nonlinearity, diverse working conditions, and high-dimensional variations. To overcome these challenges, a fusion modeling approach for ROP is proposed. First, the fuzzy C-means clustering method is applied to classify drilling data into different working con-ditions. Based on this classification, support vector regression is employed to develop ROP sub-models, effectively addressing nonlinearity. To further enhance model accuracy, an improved dung beetle optimization algorithm (IDBO) is designed to deter-mine optimal model parameters and integrate the sub-models, thereby resolving issues related to multiple working conditions and high-dimensional variations. The IDBO incorporates four key enhancements, average weight, chaos disturbance, modified local search, and re-updating of the best solution, to strength-en its global search capability. Comparative results using the IEEE CEC2017 benchmark test functions demonstrate that the proposed algorithm outperforms others in 12 test functions, highlighting its strong global optimization ability. Additionally, results from real-world drilling data validate the effectiveness of the proposed modeling approach in practical applications. © 2025 IEEE.

关键词： Clustering algorithms

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A novel task-oriented framework for dual-arm robotic assembly task

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Frontiers of Mechanical engineering 2021年第3期16卷 528-545页

作者： Zhengwei WANG Yahui GAN Xianzhong DAI School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096China

In industrial manufacturing,the deployment of dual-arm robots in assembly tasks has become a ***,making the dual-arm robots more intelligent in such applications is still an open,challenging *** paper proposes a novel framework that combines task-oriented motion planning with visual perception to facilitate robot deployment from perception to execution and finish assembly problems by using dual-arm *** this framework,visual perception is first employed to track the effects of the robot behaviors and observe states of the workpieces,where the performance of tasks can be abstracted as a high-level state for intelligent *** assembly task and manipulation sequences can be obtained by analyzing and reasoning the state transition trajectory of the environment as well as the ***,the corresponding assembly manipulation can be generated and parameterized according to the differences between adjacent states by combining with the prebuilt knowledge of the *** are set up with a dual-arm robotic system(ABB YuMi and an RGB-D camera)to validate the proposed *** results demonstrate the effectiveness of the proposed framework and the promising value of its practical application.

关键词： dual-arm assembly Al reasoning intelligent system task-oriented motion planning visual perception

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A Task Assignment Scheme Designed for Online Urban Sensing Based on Sparse Mobile Crowdsensing

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IEEE Internet of Things Journal 2025年

作者： Zeng, Hongjian Xiong, Yonghua She, Jinhua Yu, Anjun China University of Geosciences School of Automation 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 Tokyo University of Technology School of Engineering Hachioji Tokyo192-0982 Japan Jiangxi Ganyue Expressway Co. Ltd Jiangxi Nanchang330000 China

Sparse Mobile Crowdsensing (SMCS) achieves urban-scale environmental sensing by assigning tasks to workers in specific subareas and inferring global data from the collected information. However, the effectiveness of SMCS is often limited because many studies overlook workers' mobility and data collection time during subarea selection, as well as the time constraints of the sensing cycle in task assignment. This may affect the task completion timeliness and data quality. To address these issues, we develop a subarea evaluation method based on deep reinforcement learning, considering both the temporal effectiveness of sensing tasks and the importance of subarea selection for data inference. Using the subarea evaluation values derived from this method, we establish an online urban sensing task assignment model which is subject to constraints of sensing cycle time and cost budget. This model aims to find the task assignment result that minimizes data inference error by maximizing the comprehensive utility value. Considering the characteristics of the task assignment model, we propose an evolutionary algorithm named OTA-EA, which is based on an improved genetic algorithm. Its enhanced evolutionary operators can avoid generating infeasible solutions while maintaining robust search and optimization performance. Lastly, we conduct experimental evaluations of these methods on the real-world datasets. The results demonstrate that our subarea evaluation method can significantly reduce the data inference error, and our evolutionary task assignment algorithm can achieve better task assignment results than the baseline algorithms. © 2014 IEEE.

关键词： Genetic algorithms

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Coordinated Adaptive control for Coordinated Path-following Surface Vessels with a Time-invariant Orbital Velocity

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IEEE/CAA Journal of Automatica Sinica 2014年第4期1卷 337-346页

作者： Yangyang Chen Ping Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSoutheast University the Department of Electronic Information Engineering Anhui Business College

This article considers the problem of directing a family of fully actuated surface vessels to cooperatively follow a set of convex and closed orbits with a time-invariant reference orbital velocity and maintain attitude synchronization. A consensusbased adaptive control law under a bidirectional communication topology is proposed to estimate the reference orbital velocity so that the restriction that every vessel in the family must have access to the reference in the previous literature can be *** assumption of nonzero total linear speed of each vessel is removed by the use of potential function. Simulation results demonstrate the effectiveness of the proposed approach.

关键词： Coordinated adaptive control coordinated path-following attitude synchronization fully actuated surface vessels

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The effect of waist twisting on walking speed of an amphibious salamander like robot

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Acta Mechanica Sinica 2016年第3期32卷 546-550页

作者： Xin-Yan Yin Li-Chao Jia Chen Wang Guang-Ming Xie Intelligent Control Laboratory College of EngineeringPeking University Key State Laboratory for Turbulence & Complex Systems College of Engineering Peking University

Amphibious salamanders often swing their waist to coordinate quadruped walking in order to improve their crawling speed. A robot with a swing waist joint, like an amphibious salamander, is used to mimic this locomotion.A control method is designed to allow the robot to maintain the rotational speed of its legs continuous and avoid impact between its legs and the ground. An analytical expression is established between the amplitude of the waist joint and the step length. Further, an optimization amplitude is obtained corresponding to the maximum stride. The simulation results based on automatic dynamic analysis of mechanical systems（ADAMS） and physical experiments verify the rationality and validity of this expression.

关键词： Terrestrial locomotion Step length Waist twisting Walking speed

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Multimodal Image Matching based on Frequency-domain Information of Local Energy Response

arXiv

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arXiv 2025年

作者： Yang, Meng Chen, Jun Gong, Wenping Wei, Longsheng Tian, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Faculty of Engineering China University of Geosciences Wuhan430074 China Electronic Information School Wuhan University Wuhan430072 China

Complicated nonlinear intensity differences, nonlinear local geometric distortions, noises and rotation transformation are main challenges in multimodal image matching. In order to solve these problems, we propose a method based on Frequency-domain Information of Local Energy Response called FILER. The core of FILER is the local energy response model based on frequency-domain information, which can overcome the effect of nonlinear intensity differences. To improve the robustness to local nonlinear geometric distortions and noises, we design a new edge structure enhanced feature detector and convolutional feature weighted descriptor, respectively. In addition, FILER overcomes the sensitivity of the frequency-domain information to the rotation angle and achieves rotation invariance. Extensive experiments multimodal image pairs show that FILER outperforms other state-of-the-art algorithms and has good robustness and *** Codes 68U10 (Primary), 68T45, 68Wxx (Secondary) Copyright © 2025, The Authors. All rights reserved.

关键词： Mathematical transformations

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A game theoretical approach for distributed resource allocation with uncertainty

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International Journal of Intelligent Computing and Cybernetics 2017年第1期10卷 52-67页

作者： Lei Xue Changyin Sun Fang Yu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast UniversityNanjingPeople’s Republic of China

Purpose-The paper aims to build the connections between game theory and the resource allocation problem with general *** proposes modeling the distributed resource allocation problem by Bayesian *** this paper,three basic kinds of uncertainties are ***,the purpose of this paper is to build the connections between game theory and the resource allocation problem with general ***/methodology/approach-In this paper,the Bayesian game is proposed for modeling the resource allocation problem with *** basic game theoretical model contains three parts:agents,utility function,and decision-making ***,the probabilistic weighted Shapley value(WSV)is applied to design the utility function of the *** achieving the Bayesian Nash equilibrium point,the rational learning method is introduced for optimizing the decision-making process of the ***-The paper provides empirical insights about how the game theoretical model deals with the resource allocation problem uncertainty.A probabilistic WSV function was proposed to design the utility function of ***,the rational learning was used to optimize the decision-making process of agents for achieving Bayesian Nash equilibrium *** comparing with the models with full information,the simulation results illustrated the effectiveness of the Bayesian game theoretical methods for the resource allocation problem under ***/value-This paper designs a Bayesian theoretical model for the resource allocation problem under *** relationships between the Bayesian game and the resource allocation problem are discussed.

关键词： Game theory Multi-agent systems Bayesian games Resource allocation under uncertainty Paper type Research paper

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space

Safe Reinforcement Learning for Social Motor Coordination in...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Fan Yang Yuening Huang Chao Zhai Hehong Zhang China University of Geosciences Wuhan Campus School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing Houston Texas United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints.

关键词： Autism Filters Reinforcement learning Games Variable speed drives Motors Trajectory Safety Mirrors Motion control

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Secure Encoding Scheme for Consensus of Second-order Multi-Agent systems 41

Secure Encoding Scheme for Consensus of Second-order Multi-A...

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第41届中国控制会议

作者： Bingya Zhao Ya Zhang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

We consider the problem of consensus of a second-order multi-agent system in the situation where an eavesdropper tends to impact the security of the network.A secure encoding scheme that guarantees both consensus and security of the multiagent network is *** the network,the agents transmit messages to one another through digital channels,and there exists an eavesdropper whose aim is to overhear the state information of the agents in the *** of transmitting the states of themselves,the agents in the network send states of auxiliary systems to defend against the *** concept of topological entropy is utilized to restrict the eigenvalues of the encoding matrix.A sufficient condition is given to guarantee that the network achieves consensus,and the eavesdropper cannot get the accurate estimation of the state of any agent.A simulation example is given to show the performance of the agents and the eavesdropper under the designed encoding scheme.

关键词： Multi-agent system secure encoding scheme consensus topological entropy maximum transmission rate

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