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43rd Chinese control Conference, CCC 2024

作者： Wang, Guoqing Cao, Junzhe Dalian University of Technology Control Science and Engineering Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China

ISBN: (纸本)9789887581581

Aerodynamic force prediction is an important application of deep learning in the field of fluid mechanics. In this paper, a light graph neural network model with residual connections named LRGCN is designed to speed the computational process of the aerodynamic prediction. Comparing with other graph convolutional networks, the LRGCN reduces redundant operations and introduces skip connections, overcomes the limitations of traditional machine learning methods that require geometric airfoil parameters. By using CFD simulation, a dataset of aerodynamic forces for airfoil profiles was generated, where the nodes and edges of the flow field grids are abstracted to build a graph structure for aerodynamic force prediction. This study takes variations of the airfoil shape and pitch angle into consideration, enabling the prediction of lift and drag to be fast. In the numerical experiments, the LRGCN achieves the result that normalized test set loss is around 10-3 and the R2 is higher than 90%, which exhibits stronger robustness and higher accuracy than three other current convolutional models. And the LRGCN runs 60 times faster than the normal CFD method for the same prediction task, which significantly reduces time costs. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Computational fluid dynamics

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Synchronization control for Multi-Electromechanical Actuators Based on Model Predictive control 41

Synchronization Control for Multi-Electromechanical Actuator...

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第41届中国控制会议

作者： Bitong Du Shuo Zhang Jiaxing Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Model predictive control has great application potential in the field of the synchronization control due to its strong ability to solve the problem with multiple variables and strict *** this paper,mathematical model of a MIMO system of consisting with three-electromechanical actuators is established,and a relative coupling control algorithm based on model predictive control(SE-MPC) for the synchronization control of multi-electromechanical actuators has been *** synchronization errors are reduced by introducing the synchronization error items into cost function and constraints ***,the simulation verification is carried out and compared among the proposed method and the traditional model predictive control method without considering the synchronization error(NSE-MPC),as well as the relative coupled control method based on PID(RC-PID),the results illustrate preferable synchronization control performance and strong robustness of the proposed method in the comparative numerical simulation.

关键词： Multi-electromechanical actuators(Multi-EMAs) Model predictive control(MPC) Synchronization control Relative coupling control

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Stability analysis and stabilization of semi-Markov jump linear systems with unavailable sojourn-time information

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Science China(Information Sciences) 2024年第7期67卷 211-223页

作者： Xiaotai WU Yang TANG Shuai MAO Ying ZHAO School of Mathematics and Physics Anhui Polytechnic University Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of EducationEast China University of Science and Technology

This study addresses the stability and stabilization problems of discrete-time semi-Markov jump linear systems(S-MJLSs) with unavailable sojourn-time information. The sojourn-time probability mass functions(S-TPMFs) of discrete-time semi-Markov chains are no longer confined to the geometric distribution, and it is difficult to obtain accurate and comprehensive information for S-TPMFs in practice. This is because S-TPMFs are usually deduced from the statistical characteristics according to the sampled-data, while adequate samples are often costly and time consuming. In this study, when the S-TPMFs for semi-Markov chains are assumed to be unavailable, the σ-error mean square stability is investigated for discrete-time S-MJLSs with some widely used assumptions; for semi-Markov chains, only the transition probability matrix of the embedded chain is used. In addition, the existence conditions of the effective controller are provided for closed-loop systems without using the information of S-TPMFs. Numerical examples are presented to illustrate the validity of the obtained theoretical results.

关键词： semi-Markov chain semi-Markov jump linear systems σ-error mean square stability unavailable sojourn-time information

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Flow Field Prediction of Variable Geometry using a Novel Deep CNN Model with Dual-Feature of Flow Regions 43

Flow Field Prediction of Variable Geometry using a Novel Dee...

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43rd Chinese control Conference, CCC 2024

作者： Zhang, Mai J., Cao Dalian University of Technology Control Science and Engineering Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China

ISBN: (纸本)9789887581581

Flow field prediction of variable geometry aims for the precise prediction of varying flow fields with complex geometric shapes and their variations. By combining a novel deep convolutional neural network (CNN) model with a Computational Fluid Dynamics (CFD) method, the solution of the Navier-Stokes equation can be effectively approximated with a significant reduction in the corresponding computation time cost. This paper proposes an approach named AM UNet-3 for predicting the flow field of variable geometry, which can directly predict the expected flow field of new shapes after the training of deep CNN through extracting and identifying dual features of flow field regions: geometric information features and multi-class channel features. The AM UNet-3 is a convolutional neural network model that combines a U-Net variant structure with three independent decoders and attention mechanisms. The framework of U-Net can learn the complete numerical solutions of the N-S equations to velocity and pressure fields from ground-truth data. The three independent decoders are used to output the pressure field and the velocity components in the x-direction and y-direction respectively. The embedded channel attention and spatial attention mechanisms can enhance the ability of AM UNet-3 to extract fast-changing boundary layer characteristics. The performances of AM UNet-3, U-Net and UNet-3 are tested and compared on a dataset consisting of flow field data with 981 different geometric shapes. Experiment results show that AM UNet-3 gets the fastest inference and the lowest prediction error in the three methods. Compared with the standard CFD method, AM UNet-3 is able to speed up the computation more than three orders of magnitude. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Computational fluid dynamics

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Prediction of Multi-Converter Gas Holders Level in Steel Enterprises based on Mechanism and Data 43

Prediction of Multi-Converter Gas Holders Level in Steel Ent...

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43rd Chinese control Conference, CCC 2024

作者： Yan, Yaliang Chen, Long Zhao, Jun Wang, Wei Dalian University of Technology School of Control Science and Engineering Dalian116024 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116024 China

ISBN: (纸本)9789887581581

Linz Donawitz converter gas (LDG) is an important secondary energy source in iron and steel enterprises. The accurate prediction of converter gas holder level is of great significance for the optimal scheduling of the LDG systems. Considering that there are multi-operating conditions caused by the affection of different gas holders from each other in a multiple gas holders system, this paper proposes a mechanism and data-based converter gas holder level prediction method, in which via physical mechanism analysis the operating conditions as well as their switching logics are built according to different pressures in each gas holder and valve states. Then, the least squares support vector machine (LSSVM) is employed to establish gas holders level prediction models for each operating condition. The actual operation data in an iron and steel plant of China are employed for simulation experiments. The results show that the proposed method not only can effectively identify the operating conditions of dual gas holders system, but also can achieve higher prediction accuracies compared to those of other prediction methods, providing effective guidance for the scheduling of the LDG systems. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Iron and steel plants

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Multi-level DEM study on silo discharge behaviors of non-spherical particles

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Particuology 2023年第11期82卷 179-191页

作者： Lei Xu Xiukai Wu Jingyin Liang Shuai Wang Shiyi Bao Institute of Process Equipment and Control Engineering College of Mechanical EngineeringZhejiang University of TechnologyHangzhou310032China Engineering Research Center of Process Equipment and Remanufacturing Ministry of EducationChina State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou310027China

The silo discharge of non-spherical particles has been widely practiced in engineering processes, yet the understanding of multi-level mechanisms during solid transportation is still lacking. In this study, a high-fidelity super-ellipsoid Discrete Element Method (DEM) model is established to investigate the discharge behaviors of non-spherical particles with different size distributions. After the comprehensive model validations, we investigated the effects of particle shape (aspect ratio and particle sharpness) on the particle level discharge behaviors. The discharge rates of the ellipsoid particles used in the current work are larger than the spherical particles due to the larger solid fraction. The discharge rates of the cuboid-like particles are determined by the combined effect of the solid fraction and the contact force. Parcel level data show that the translational movements of the ellipsoid particles are more ordered, which is supported by the global level data. Strong correlations exist between the particle level and parcel level data, especially the ellipsoid particles and the large particles in the polydispersed cases.

关键词： Multi-level study Non-spherical particle Numerical simulation Silo discharge Granular flow

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Time-scheduled observer design for switched linear systems with unknown inputs

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Science China(Information Sciences) 2022年第7期65卷 265-266页

作者： Shuang SHI Zhongyang FEI Xudong ZHAO College of Automation Engineering Nanjing University of Aeronautics and Astronautics Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology

Dear editor, Since uncertain disturbance, actuator faults and unmodeled dynamics can all be viewed as unknown inputs in various practical systems, the issue of unknown input observer design is of great significance. Meanwhile, switched systems have attracted extensive attention, which are prevailingly motivated by superior capabilities in modeling numerous practical systems possessing switching characteristics. Recently, the state observation for switched systems with unknown inputs has attracted considerable attention [1–5].

关键词： switched linear systems unknown inputs admissible edge-dependent average dwell-time multiple discontinuous Lyapunov-like functions observer design

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Joint optimization of Production and Shipping for Small Orders Considering Less-Than-Container Loading 4th

Joint Optimization of Production and Shipping for Small Orde...

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4th International Conference on Resources and Environmental Research, ICRER 2022

作者： Tian, Yajing Wang, Guoqiang Chen, Yingying Luo, He School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization & Intelligent Decision-Making Ministry of Education Hefei China

ISBN: (纸本)9783031318078

This paper introduces a joint optimization problem of production and shipping for overseas small orders considering less-than-container loading (LCL) in manufacturing enterprises. The problem consists of finding a production schedule together with a LCL shipping scheme simultaneously to minimize the total cost. An integer programming model is developed, and the genetic algorithm of enhanced elite reservation (SEGA) is used to solve large-sized instances. Besides, the performance of SEGA is compared with the classical genetic algorithm (SGA) and stallion genetic algorithm (stud GA). It is statistically shown that SEGA outperforms other algorithms in finding near-optimal solutions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Loading

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Robust Stochastic Configuration Network Based Prediction Model of Total Nitrogen Content in Crude Oil 5

Robust Stochastic Configuration Network Based Prediction Mod...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Lu, Jun Feng, Min Ding, Jinliang Zhang, Xiaoling Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116024 China

ISBN: (纸本)9798350325294

The refineries usually process the blending crude oil at present. Blending crude oil leads to the increased uncertainties of physical properties of crude oil. This paper presents a robust stochastic configuration network (SCN) based prediction model for total nitrogen content in crude oil. First, the robust SCN based on Bayesian framework is proposed. In the Bayesian framework, the noise and outliers are assumed to be the mixture of two Gaussian distributions to improve the robustness of SCN. Then, to solve the problem that there are no analytical solutions of parameters due to the assumption of mixture of Gaussian distributions, parameters of the proposed robust SCN are estimated by the expectation maximization (EM) algorithm. Experiments using the real-world data collected from a refinery are carried out. The results indicate that the proposed approach has better accuracy and robustness. © 2023 IEEE.

关键词： Crude oil

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The Evolution of Cooperation in Multiplayer Snowdrift Games with Environmental Feedback 43

The Evolution of Cooperation in Multiplayer Snowdrift Games ...

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43rd Chinese control Conference, CCC 2024

作者： Sun, Tao Liang, Haili Yu, Xiaotong Zhou, Zhao Xu, Yang Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai200444 China East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education Shanghai200237 China

ISBN: (纸本)9789887581581

Human societies and natural environments form a complex ecological system, in which human activities can change the ecological environment, the changes in the ecological environment can influence human social activities in reverse. This paper introduces a punitive mechanism as environmental feedback into co-evolutionary systems, and proposes a replicator dynamic model which aims to explain the evolutionary strategies adopted by populations for the multiplayer snowdrift games. We obtain the necessary and sufficient condition for the existence and stability of the internal equilibrium point by studying on the Jacobian matrix, and the effectiveness of the theoretical results is examined by numerical simulations. We identify that the threshold parameter in multiplayer snowdrift games determines the evolution of the closed-loop system. Specifically, the system exhibits limit cycles when the threshold is small enough. As the threshold increases, the system converges to a stable internal equilibrium point. Finally, if the threshold reaches a sufficiently large value, the proportion of cooperators in the population is high, while the group of punishers becomes extinct, indicating the loss of environmental feedback. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Anthropogenic

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