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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent Systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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Multi-CODP decision models for supplier selection and order allocation in customized logistics service supply chain

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Neural Computing and Applications 2024年第19期36卷 11097-11119页

作者： Hu, Xiaojian Xu, Liangcheng Yao, Gang Wu, Zhening School of Management Hefei University of Technology Tunxi Anhui Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Tunxi Anhui Hefei230009 China

To address the problem of positioning customer order decoupling point (CODP) in customized logistics service supply chain and to provide logistics service integrators (LSI) with various CODP decision-making and supplier selection solutions. We consider LSI, logistics service providers (LSPs) and customers and propose multiobjective nonlinear team optimization models for multi-CODP location, including minimizing the cost to the LSI and maximizing the synthetic satisfaction of LSPs and customers. This paper adopts an improved nondominated sorting genetic algorithm (NSGA-II), in which the key modules such as the crossover operations, chromosome structure and mutation operations are reconstructed, to solve the team models and investigate the Pareto-optimal front for the two objectives. To demonstrate the validity of NSGA-II and the reliability of mathematical models, cases from a specific dataset are generated and solved. Moreover, a classic genetic algorithm (GA) is applied to solve for the two objectives separately. The optimal solutions found by GA are f1 = 2027.491, f2 = 0.7704 and f1 = 2454.512, f2 = 0.8909. The corresponding optimal solutions in the Pareto-optimal solution set are f1 = 2053.675, f2 = 0.7715 and f1 = 2427.114, f2 = 0.8843. We find that the optimal solutions provided by GA cannot dominate any solution in the Pareto-optimal solution set, indicating that the results are valid and sufficiently convergent. In summary, the results of this paper provide LSI with easy access to various supplier selection schemes with multi-CODP, which is essential to reduce the cognitive burden on decision makers and address the diverse customization needs of many challenging real-world logistics issues. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Genetic algorithms

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A Safety-Enhanced Multi-Modal Objectives Motion Fusion Method for Autonomous Retraction in Robotic Surgery

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 15990-16000页

作者： Shi, Yudong Mo, Hangjie Xiao, Xilin Fang, Jin Li, Ling Min, Kang Li, Xiaojian Hefei University of Technology School of Management Hefei China Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education) Hefei China

In minimally invasive surgery (MIS), tissue retraction is critical for exposing the surgical site and facilitating pathological tissue excision. However, tissue retraction in MIS is subject to multiple constraints, including restricted field of view, non-damaging tissue retraction force, and limited instrument operating range, which hinder the safe and continuous retraction of tissue during robotic-assisted surgery. This paper introduces a novel autonomous retraction method for MIS, capable of safely retracting tissue within the aforementioned multiple constraints, assisting the surgeon in tissue excision. The method takes into account information from three different modalities: vision, force, and position. Based on these, three distinct control objectives are defined: retraction angle, retraction force, and safety space constraints, with an individual controller and model-predictive evaluation function designed for each objective. We propose a novel multi-objective motion fusion strategy designed to balance three distinct control objectives. This strategy evaluates the sensitivity of each objective to changes in the system state by comparing the gradients of their respective prediction evaluation functions and fuses the control inputs of the individual controllers. The proposed method allows for rapid addition or removal of objectives without altering the algorithmic framework. Experiments with phantoms and ex vivo animal tissue are conducted on robotic platform to validate the effectiveness of the proposed method in various configurations. Note to Practitioners—The motivation of this study is to address the challenge of autonomous tissue retraction in robotic-assisted laparoscopic surgery under multiple constraints. Existing methods primarily focus on single objectives and overlook the conflicts and coordination required among multi-modal objectives such as retraction angle, force, and safety space constraints. These limitations reduce the safety of robotic syste

关键词： motion fusion robot autonomy surgical robot Tissue retraction

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Design and optimization Analysis of an Adaptive Knee Exoskeleton

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Chinese Journal of Mechanical Engineering 2024年第5期37卷 387-408页

作者： Xinhua Yang Sheng Guo Peiyi Wang Yifan Wu Lianzheng Niu Duxin Liu School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Key Laboratory of Vehicle Advanced Manufacturing Measuring and Control TechnologyMinistry of EducationBeijing Jiaotong UniversityBeijing 100044China

To solve the problem of undesired relative motion of human-machine interaction positions caused by misalignment of the human-machine joints rotation axis of the knee exoskeleton,this study designed an adaptive knee exoskeleton based on a gear-link mechanism(GLM)by considering the human body as a component of the exoskeleton ***,the concept of the wearable area(WA)was proposed,which transformed the operation of aligning the exoskeleton rotation axis with the human knee joint rotation axis into a"face alignment point"in the sagittal plane,reducing the difficulty of aligning the human-machine joint rotation *** the kinematic analysis of GLM,the phenomenon of instantaneous movement of the central axis of the human knee joint was *** on the kinematic model,the WA,velocity transfer ratio,and initial position static stiffness of GLM were *** NSGA-II optimization algorithm was used to optimize the size parameters of GLM,which increased the WA by 18.4%,the average velocity transfer ratio by 4.98%,and the average initial position static stiffness by 6.01%.Finally,the ability of the exoskeleton to absorb movement displacement(MD)was verified through simulation,and the good human-machine kinematic compatibility of the exoskeleton was verified through wearable tests conducted on the initial mechanism principle prototype.

关键词： Adaptive knee exoskeleton Gear-link mechanism Wearable area optimization Simulation

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Enhancement of weathered crust elution-deposited rare earth ores leaching process with PQ-10 addition

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Journal of Rare Earths 2025年第1期43卷 180-190,I0007页

作者： Aoyang Sha Huifang Yang Zhengyan He Zhigao Xu Chenjie Wu Ming Wu Ru'an Chi Key Laboratory of Catalysis and Energy Materials Chemistry of Ministry of Education Key Laboratory of Resources Conversion and Pollution Control of the State Ethnic Affairs Commission&Hubei Key Laboratory of Catalysis and Materials ScienceCollege of Resources and Environmental ScienceSouth-Central Minzu UniversityWuhan430074China Key Laboratory for Green Chemical Process of Ministry of Education School of Resources&Safety EngineeringWuhan Institute of TechnologyWuhan 430073China

To solve the problems of the long development period,low mass transfer efficiency and high impurity conte nt in the in-situ leaching process of weathe red crust elution-deposited rare earth ores(WCE-DREO),cationic hydroxyethyl cellulose(PQ-10)was composited with conventional leaching agent ammonium sulfate((NH_(4))_(2)SO_(4))to form a novel composite leaching *** effects of PQ-10 concentration,leaching temperature and leaching flow rate of the composite leaching agent on the leaching kinetics and mass transfer processes of rare earth(RE)and aluminum(Al)were *** to the single leaching agent(NH_(4))_(2)SO_(4),the composite leaching agent(2 wt%(NH_(4))_(2)SO_(4)+0.02 wt%PQ-10)can reduce the RE leaching equilibrium time from 465 to 130 min and increase the RE leaching efficiency and decrease the Al leaching *** also facilitates the leaching process of WCE-DREO by increasing the peak concentrations of RE and Al,reducing the theoretical tower plate height(HETP)and improving the leaching mass transfer *** is indicated that PQ-10 can promote the leaching of *** leaching process of the composite leaching system conforms to the diffusion kinetic control *** the PQ-10 concentration is in the range of 0.005 wt%-0.020 wt%,the reaction orders of RE and Al are 0.73 and 0.54,respectively,which shows a positive effect on the leaching velocity;when the PQ-10 concentration is in the range of 0.030 wt%-0.060 wt%,the reaction orders of RE and Al are-1.16 and-0.75,respectively,which show a negative effect on the leaching *** the range of 10-50℃,the apparent activation energies of RE and Al are 15.02 and 17.31 kJ/mol,respectively,and the higher the leaching temperature,the smaller the HETP and the higher the leaching velocity and mass transfer *** increase in leaching flow rate contributes to the increase in the longitudinal diffusion velocity of the leaching agent within WCE-DREO,causing a shorter time for RE

关键词： Cationic hydroxyethyl cellulose Weathered crust elution-deposited rare earthores Leaching Novel compositeagent

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Single-factor Multi-level Fermentation Model Based on Linear Parameter Varying Finite Impulse Response

Single-factor Multi-level Fermentation Model Based on Linear...

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2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Wang, Xuezheng Chen, Xiang Wang, Xiaogang Liu, Fei Key Laboratory for Advanced Process Control of Light Industry of the Ministry of Education Jiangnan University Wuxi214122 China

ISBN: (纸本)9781837242689

The fermentation process of Corynebacterium glutamicum exhibits complex dynamic characteristics such as nonlinearity and strong coupling, which makes it difficult to establish an accurate dynamic model, thus making the system challenging to optimize and control. Considering nonlinear dynamic processes can be well described by Linear Parameter-Varying (LPV) models, this work suggests a method for modeling the Corynebacterium glutamicum fermentation process based on Linear Parameter Varying Finite Impulse Response (LPV-FIR). Three product (succinic, lactic, and acetic) concentrations and their dynamic interactions with the oxygen transfer coefficient (KLA) are described. Experiments prove that this model can describe the dynamic changes of all the variables in the fermentation process, which has a certain accuracy and robustness. © The Institution of Engineering & technology 2024.

关键词： Impulse response

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A composite quantile regression long short-term memory network with group lasso for wind turbine anomaly detection

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Journal of Ambient Intelligence and Humanized Computing 2023年第3期14卷 2261-2274页

作者： Xu, Qifa Wu, Dongdong Jiang, Cuixia Wang, Xiangxiang School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei230009 China

Wind turbine anomaly detection is an important but challenging work. Though deep learning is promising in this filed, it may fail for large error distributions and often lacks interpretability due to its complex structure. To this end, we develop a composite quantile regression long short-term memory network with group lasso (CQR-LSTM-GL). The CQR-LSTM-GL model extends the LSTM network to the quantile regression framework, which makes LSTM always valid regardless of the error distribution. Additionally, the CQR-LSTM-GL model adopts the group lasso method to compress the network structure and select key features. To illustrate its efficacy, we conduct a numerical experiment on the public server machine datasets. The experimental results show that the CQR-LSTM-GL model is not only slightly better than several competitive models in anomaly detection performance, but also far ahead in sparsity performance. The sparsity of CQR-LSTM-GL is 1.63 times that of CQR-LSTM-L1, and much more than that of CQR-LSTM. We then apply the CQR-LSTM-GL model to the anomaly detection of a wind turbine using the real Supervisory control and Data Acquisition data, where all three anomalies are identified. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Long short-term memory

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Multicriteria game approach to air-to-air combat tactical decisions for multiple UAVs

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Journal of Systems Engineering and Electronics 2023年第6期34卷 1447-1464页

作者： JIANG Ruhao LUO He MA Yingying WANG Guoqiang School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization&Intelligent Decision-making Ministry of EducationHefei 230009China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei 230009China

Air-to-air combat tactical decisions for multiple unmanned aerial vehicles(ACTDMU)are a key decision-making step in beyond visual range *** influencing factors,strong antagonism and real-time requirements need to be considered in the ACTDMU *** this paper,we propose a multicriteria game approach to *** approach consists of a multicriteria game model and a Pareto Nash equilibrium *** this model,we form the strategy profiles for the integration of air-to-air combat tactics and weapon target assignment strategies by considering the correlation between them,and we design the vector payoff functions based on predominance *** propose a algorithm of Pareto Nash equilibrium based on preference relations using threshold constraints(PNE-PRTC),and we prove that the solutions obtained by this algorithm are refinements of Pareto Nash equilibrium *** numerical experiments indicate that PNE-PRTC algorithm is considerably faster than the baseline algorithms and the performance is *** on large-scale instances,the Pareto Nash equilibrium solutions can be calculated by PNEPRTC algorithm at the second *** simulation experiments show that the multicriteria game approach is more effective than one-side decision approaches such as multiple-attribute decision-making and randomly chosen decisions.

关键词： tactical decision multicriteria game preference relation Pareto Nash equilibrium.

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Automatic Labeling of In-Situ Crystal Images based on Lightweight Network Bisenetv2 43

Automatic Labeling of In-Situ Crystal Images based on Lightw...

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43rd Chinese control Conference, CCC 2024

作者： Yan, Luyao Fan, Ji Liu, Tao Wang, Hui Zhao, Zhenbang Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Dalian University of Technology Institute of Advanced Control Technology Dalian116024 China

ISBN: (纸本)9789887581581

To enhance the efficiency and accuracy of in-situ crystal image annotation for building up a model to monitor the crystal growth process during cooling crystallization, a deep learning based automatic labeling method is proposed by using the lightweight network Bisenetv2. The image segmentation is conducted by the lightweight network Bisenetv2, for which a hyperparameter optimization (HPO) and class balance training strategy is presented to improve the segmentation accuracy on in-situ captured images. The trained model is converted into the open neural network exchange (ONNX) format to reduce the implemental dependence on any specific or complex environmental configurations. Furthermore, a software package is developed to embed the ONNX format model for implementation. Additionally, a multi-stage image processing algorithm is provided to enhance image quality for analysis, based on the characteristics of in-situ crystal images captured during the crystallization process. Correction algorithms for poorly segmented crystal contours are also designed, resulting in a final mean intersection over union (mIOU) of 0.8216, with the automated annotation process taking approximately 1 second per image. Experimental results on in-situ images of β form L-glutamic acid (β-LGA) captured from different batches of crystallization validate the effectiveness and robustness of the proposed method. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Image segmentation

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Automated Cross-modal Registration Algorithm For Liver Surgery Navigation 24

Automated Cross-modal Registration Algorithm For Liver Surge...

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2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Li, Ling Chen, Yulu Shen, Ziming Mo, Hangjie Li, Xiaojian Hefei University of Technology Anhui Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Anhui Hefei China

ISBN: (纸本)9798400710681

By overlaying preoperative models and their internal structures onto endoscopic images, cross-modal registration methods restore a surgeon’s ability to perceive three-dimensional information in laparoscopic scenes, providing precise surgical navigation. Many cross-modal registration and surgical navigation techniques are heavily reliant on manually annotated landmark information. An automated preoperative-to-intraoperative cross-modal registration pipeline for 3D-2D registration in laparoscopic liver interventions is proposed in this paper, eliminating manual intervention. Firstly, two convolutional neural networks are trained to autonomously obtain contours as landmarks from preoperative models and intraoperative endoscopic images. Secondly, an improved Random Sample Consensus-based perspective-n-points method with segmentation constraints is proposed to calculate the transformation from the preoperative model to the endoscopic coordinate system using marked points of key anatomical structures. Finally, the preoperative model is projected onto the intraoperative coordinate system to achieve augmented reality visual guidance. In experiments conducted on a public liver registration dataset, the method proposed in this paper achieves comparable results to registration methods based on manual annotations, validating the effectiveness of the proposed pipeline. © 2024 Copyright held by the owner/author(s).

关键词： Augmented reality

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