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15th International Conference on Computer Modeling and Simulation, ICCMS 2023

作者： Li, Jun Zhou, Yong Liu, Xin Liu, Jinsong Li, Qing Kong, Xiangjun Niu, Guankai Department of Automation Tsinghua University Beijing China Exchange and Cooperation Department China Industrial Control Systems Cyber Emergency Response Team Beijing China SINOMACH Intelligence Technology Research Institute Co. Ltd. Beijing China Avic Manufacturing Technology Institute Beijing China

ISBN: (纸本)9798400707919

With the accelerated integration of the new generation information technology and manufacturing industry, the performance of production equipment continues to be optimized, evolved and upgraded iteratively. The production equipment model presents a multi-dimensional, multi-level, full life cycle integration development trend, which has become the key to improve the innovative capability and digital management level of production equipment. Aiming at the problems of multiple types of production equipment models, such as complex structure, difficult integration and low application efficiency, this study analyzed the relationship and interaction mechanism among production equipment models from the perspectives of life cycle, hierarchical structure and multi-dimension, and built a production equipment model architecture. Based on the model architecture of production equipment, a general multi-dimensional fusion framework of production equipment models was proposed, which takes the mechanism model as the core. This study can provide reference for the construction, integration and application of production equipment models. © 2023 ACM.

关键词： Integration

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Landslide Sensitivity Mapping Based on One-Dimensional Residual Convolutional Neural Networks

Landslide Sensitivity Mapping Based on One-Dimensional Resid...

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2022 Chinese automation Congress, CAC 2022

作者： Ke, Yougang Lu, Chengda Wu, Min Yu, Wanke Niu, Ruiqing School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Institute of Geophysics and Geomatics China University of Geosciences Wuhan China

ISBN: (纸本)9781665465335

Landslide is a common geological disaster. Landslide sensitivity mapping (LSM) is the key technology for landslide monitoring, early warning and risk assessment. Deep learning shows good performance in feature extraction. This paper proposes a one-dimensional residual convolution neural network (1DRCNN), which takes Yunyang County, Chongqing City, China, located in the Three Gorges Reservoir area as the research area. Extracting 12 evaluation factors from multi-source remote sensing data and building a training set. The spatial probability of landslide occurrence is quantitatively predicted by the proposed model, and finally, the landslide sensitivity mapping is generated. Compared with the common machine learning models SVM and logistic regression, the results show that the AUC (area under curve) and accuracy of 1D-RCNN are 0.9860 and 93.38%, respectively, which proving that this method is effective and can provide a reference for disaster prevention and reduction. © 2022 IEEE.

关键词： Landslides

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A multiple-time-scale control strategy for burden distribution and blast supply of a BF

A multiple-time-scale control strategy for burden distributi...

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Chinese control and Decision Conference, CCDC

作者： Yunpeng Guo Jianqi An Guoyu Zhao Min Wu Qingyi Wang 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 Wuhan China

The operations of blast furnaces (BFs) are very vital for the long-term stability of the iron making process. The burden distribution and blast supply are the two major operation systems of BFs. At present, the researches are lack effective adjustment methods for the BF operations combined with burden distribution and blast supply. The burden distribution affects the iron making process on a long time scale, while the blast supply affects the iron making process on a short time scale. This paper presents a multi-time sampling-data adjustment strategy for the BF operations aiming at optimizing GUR on multiple time scales. First, this paper analyzes the relationship between the gas utilization ratio (GUR) and the burden distribution, the blast supply on multiple time scales. Then, this paper establishes a prediction model of GUR on the long time scale and the short time scale based on autoregressive integrated moving average (ARIMA). Next, this paper provides a control strategy of burden distribution and a control strategy of blast supply by a prediction model based on support vector regression (SVR). Finally, this paper makes experiments and applies this method in a real-world BF. The analysis of the results shows the control strategy of the BF operations provides a good guide on making a suitable decision for burden distribution and blast supply.

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An Error Correcting Output Code Algorithm Based on Hierarchical Clustering for Lithology Identification

An Error Correcting Output Code Algorithm Based on Hierarchi...

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第43届中国控制会议

作者： Ao Li Xi Chen School of Rail Transit Hunan University of Technology Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems.Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Lithology identification serves as a crucial foundation for the precise exploration and safe exploitation of geological resources. However, challenges arise from the inherent imbalance and overlap present in logging data, making the accurate identification of lithology a complex task. Addressing these challenges effectively, this paper introduces a novel algorithm,the Error Correcting Output Code algorithm based on Hierarchical Clustering(HC-ECOC). The proposed algorithm initially formulates a coding matrix using distance and overlap measures between class clusters. Subsequently, it extends the length of the coding matrix by considering both the accuracy of the integrated classifier and the diversity among base classifiers. To evaluate the efficacy of the proposed method, comparisons were conducted with alternative algorithms using UCI datasets and an authentic lithology dataset. The results unequivocally demonstrate the superior performance of our algorithm.

关键词： Lithology Identification Error Correcting Output Code Hierarchical Clustering

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Optimization of the Landslide Susceptibility Model based on Deep Forest and Twice-Sample

Optimization of the Landslide Susceptibility Model based on ...

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2022 Chinese automation Congress, CAC 2022

作者： Yang, Yuelin Yu, Wanke Liu, Zepeng Zhao, Lingran Lu, Chengda Wu, Min Niu, Ruiqing China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China China University of Geosciences Institute of Geophysics and Geomatics Wuhan China

ISBN: (纸本)9781665465335

In the analysis of regional landslide susceptibility, the geological data used usually have the characteristics of multiplicity and nonlinearity. At the same time, in the past researches, the selection of non-landslide units in the training set is usually random or subjective, and there is no guarantee sample accuracy. In this paper, the deep forest algorithm combined with the twice-sample method is used to evaluate the landslide susceptibility in the Zigui Badong area of the Three Gorges Reservoir area. First, 11 landslide impact factors were selected according to the geological data to initially construct a sample set, and the cleaned data set was obtained by twice-sample. After dividing the training set and the test set, the deep forest model was used to predict the landslide susceptibility and evaluate the accuracy. The results show that the AUC of the susceptibility prediction model built using the deep forest is 1%-10% higher than that of GBDT, MLP and other methods, while the Twice-Sample method improves the AUC by 2%. © 2022 IEEE.

关键词： Landslides

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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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Distributed multi-timescale algorithm for nonconvex optimization problem: A control perspective

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Neural Networks 2025年 186卷 107257页

作者： Shi, Xiasheng Liu, Jian Sun, Changyin School of Artificial Intelligence Anhui University Hefei230106 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 Automation Southeast University Nanjing210096 China

The distributed nonconvex constrained optimization problem with equality and inequality constraints is researched in this paper, where the objective function and the function for constraints are all nonconvex. To solve this problem from a control perspective, a virtual reference-based convex penalty function is added to the augmented Lagrangian function. Then, based on the primal–dual technique, a two-timescale distributed approach is designed based on the consensus scheme. The slower subsystem aims to ensure the optimality, and the faster subsystem intends to guarantee the stability. Finally, three cases are presented to illustrate the approach's effectiveness. © 2025 Elsevier Ltd

关键词： Consensus algorithm

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Dynamic Tip-Over Avoidance Method for Mobile Manipulators Based on the Extended Zero-Moment Point Algorithm for Human–Robot Collaboration

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Journal of Computing and Information Science in Engineering 2025年第5期25卷 051003页

作者： Tao, Yong Liu, Haitao Song, Yian Deng, Changyi Wang, Baicun Zheng, Pai School of Mechanical Engineering and Automation Beihang University Beijing 100191 China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing 100040 China School of Mechanical Engineering Zhejiang University Hangzhou 310030 China Research Institute for Advanced Manufacturing Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Hong Kong

Human–robot collaboration (HRC), as an important role in intelligent manufacturing, is widely utilized in modern factories. Mobile manipulators offer greater flexibility due to the ability to simultaneously move their bases and arms. This provides them an advantage in facing challenging tasks such as flexible production and intelligent manufacturing. The environment of modern factories is complex, with slopes and thresholds at the entrance. Stability plays a fundamental role in complex environments. Therefore, for the future deployment and application of mobile manipulator in HRC, a novel dynamic tip-over avoidance method is proposed for mobile manipulators based on the extended zero-moment point (ZMP) algorithm. This method extends the traditional ZMP stability criterion into three dimensions, deriving a system-wide three-dimensional (3D) zero-moment point. The integration of the extended ZMP with redundant features facilitates adaptive weight matrix adjustments, enabling the robot to adapt its motion based on environmental constraints, thus preventing instability such as tip-over. Simulation verification is carried out withcoppeliasim. Experimental verification is performed using the MR2000 + FR3 mobile manipulator. The results confirm that the extended ZMP algorithm effectively prevents tipping in complex environments.

关键词： tip-over avoidance null-space projection Weight (Mass) mobile manipulator Stability Manipulators Robots human–robot interfaces/interactions velocity controlled manufacturing automation extended ZMP Algorithms

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Attentive online sequential extreme learning machine for nonlinear dynamic process monitoring

Attentive online sequential extreme learning machine for non...

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第34届中国过程控制会议

作者： Jingxin Zhang Yuying Cao Hai Zhou Department of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of Education Department of Automation Southeast University New Energy Research Center China Electric Power Research Institute

This paper provides a new monitoring method based on the attention mechanism and online sequential extreme learning machines(OS-ELM) for nonlinear dynamic process,referred as attentive ***-ELM provides the prediction of outputs and the update of parameters by sequential *** cope with nonlinearity,the attention mechanism is utilized to map data to a high-dimensional feature *** effect of the attention mechanism and the single hidden layer feedforward network trained with OS-ELM work collaboratively in monitoring the real-time process data to detect possible *** addition,fault detection rate and false alarm rate are adopted to evaluate the monitoring *** effectiveness of the proposed method is illustrated by a typically complicated industrial system.

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Switched max-plus linear-dual inequalities for makespan minimization: the case study of an industrial bakery shop 1

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IFAC-PapersOnLine 2023年第2期56卷 8628-8634页

作者： Davide Zorzenon Nataliia Zaiets Jörg Raisch Control Systems Group Technische Universität Berlin Germany Department of Automation and Robotics Systems National University of Life and Environmental Sciences of Ukraine Kyiv Science of Intelligence Research Cluster of Excellence Berlin Germany

In this paper, an industrial bakery shop is modeled by switched max-plus linear-dual inequalities (SLDIs). SLDIs are timed discrete event systems suitable for describing flow shops with time-window constraints and switching operating modes, where each mode corresponds to a job type. We consider the scheduling problem of minimizing the makespan of the shop, and we show that the application of methods based on the max-plus algebra leads to a faster solution compared to standard techniques. The results of the paper are general, in the sense that they can be applied to any permutation flow shop with time-window constraints.

关键词： Scheduling Food industry Max-plus algebra Discrete event systems

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