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Chinese control Conference (CCC)

作者： Shuai Yan Shoulin Hao Haichen Yu Tao Liu Bin Yan Yihui Gong Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China Institute of Advanced Control Technology Dalian University of Technology Dalian China

In this paper, a radial basis function neural network (RBFNN) based active disturbance rejection control (ADRC) scheme is proposed for continuous-time systems with unknown nonlinear dynamics and time-varying disturbance. By using RBFNN to online approximate the unknown nonlinear dynamics, a novel nonlinear extended state observer (ESO) is firstly designed to estimate the total disturbance consisting of time-varying external disturbance and RBFNN approximation error. Then, an anti-disturbance feedback control law together with a tracking differentiator is designed to counteract the total disturbance in a feedforward manner. The bounded convergence of the closed-loop system and ESO as well as the estimation errors of the weighting vector are rigorously analyzed based on the Lyapunov stability theory. A case study is carried out to demonstrate the effectiveness and merit of the proposed design, in contrast to the conventional ADRC.

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Functional meniscus reconstruction with biological and biomechanical heterogeneities through topological self-induction of stem cells

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Bioactive Materials 2024年第6期36卷 358-375页

作者： Mingze Du Kangze Liu Huinan Lai Jin Qian Liya Ai Jiying Zhang Jun Yin Dong Jiang Department of Sports Medicine Peking University Third HospitalInstitute of Sports Medicine of Peking UniversityBeijing Key Laboratory of Sports InjuriesEngineering Research Center of Sports Trauma Treatment Technology and DevicesMinistry of EducationBeijingChina The State Key Laboratory of Fluid Power Transmission and Control Systems Key Laboratory of 3D Printing Process and Equipment of Zhejiang ProvinceSchool of Mechanical EngineeringZhejiang UniversityZhejiang310058China Department of Engineering Mechanics Key Laboratory of Soft Machines and Smart Devices of Zhejiang ProvinceZhejiang UniversityZhejiang310058China School of Chemistry Chemical Engineering and BiotechnologyNanyang Technological University639798Singapore

Meniscus injury is one of the most common sports injuries within the knee joint,which is also a crucial pathogenic factor for osteoarthritis(OA).The current meniscus substitution products are far from able to restore meniscal biofunctions due to the inability to reconstruct the gradient heterogeneity of natural meniscus from biological and biomechanical ***,inspired by the topology self-induced effect and native meniscus microstructure,we present an innovative tissue-engineered meniscus(TEM)with a unique gradient-sized diamond-pored microstructure(GSDP-TEM)through dual-stage temperature control 3D-printing system based on the mechanical/biocompatibility compatible high M_(w) poly(ε-caprolactone)(PCL).Biologically,the unique gradient microtopology allows the seeded mesenchymal stem cells with spatially heterogeneous differentiation,triggering gradient transition of the extracellular matrix(ECM)from the inside ***,GSDP-TEM presents excellent circumferential tensile modulus and load transmission ability similar to the natural *** implantation in rabbit knee,GSDP-TEM induces the regeneration of biomimetic heterogeneous neomeniscus and efficiently alleviates joint *** study provides an innovative strategy for functional meniscus *** self-induced cell differentiation and biomechanical property also provides a simple and effective solution for other complex heterogeneous structure reconstructions in the human body and possesses high clinical translational potential.

关键词： Tissue-engineered meniscus Functional reconstruction Mesenchymal stem cells Heterogeneity Topology structure

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A Fast Generation Algorithm of Communication Topology for Three-dimensional Optimally Persistent Formation 33

A Fast Generation Algorithm of Communication Topology for Th...

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第33届中国控制与决策会议

作者： Guoqiang Wang Qianwei Lv Xiaoduo Li Xin Cao He Luo School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Engineering Research Center for Intelligent Decision-making & Information Systems Technologies Ministry of Education Key Laboratory of Urban ITS Technology Optimization and Integration Ministry of Public Security of China

ISBN: (纸本)9781665431293

To solve the communication topology generation problem of three-dimensional optimally persistent formation with leader constraint,a fast generation algorithm based on minimum cost arborescence,arc addition and path reverse operation is *** with the existing algorithms,this algorithm has a shorter calculation ***,the simulation results further verify the correctness and effectiveness of the algorithm.

关键词： Communication topology Leader constraint Three-dimensional optimal persistent formation Minimum cost arborescence Arc addition Path reverse operation

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Toxicity prediction and classification of Gunqile-7 with small sample based on transfer learning method

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Computers in Biology and Medicine 2024年 173卷 108348-108348页

作者： Zhao, Hongkai Qiu, Sen Bai, Meirong Wang, Luyao Wang, Zhelong Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China Key Laboratory of Ministry of Education of Mongolian Medicine RD Engineering Inner Mongolia Minzu University Tongliao028000 China

Drug-induced diseases are the most important component of iatrogenic disease. It is the duty of doctors to provide a reasonable and safe dose of medication. Gunqile-7 is a Mongolian medicine with analgesic and anti-inflammatory effects. As a foreign substance in the body, even with reasonable medication, it may produce varying degrees of adverse reactions or toxic side effects. Since the cost of collecting Gunqile-7 for pharmacological animal trials is high and the data sample is small, this paper employs transfer learning and data augmentation methods to study the toxicity of Gunqile-7. More specifically, to reduce the necessary number of training samples, the data augmentation approach is employed to extend the data set. Then, the transfer learning method and one-dimensional convolutional neural network are utilized to train the network. In addition, we use the support vector machine-recursive feature elimination method for feature selection to reduce features that have adverse effects on model predictions. Furthermore, due to the important role of the pre-trained model of transfer learning, we select a quantitative toxicity prediction model as the pre-trained model, which is consistent with the purpose of this paper. Lastly, the experimental results demonstrate the efficiency of the proposed method. Our method can improve accuracy by up to 9 percentage points compared to the method without transfer learning on a small sample set. © 2024 Elsevier Ltd

关键词： Toxicity

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A Force-driven and Vision-driven Hybrid control Method of Autonomous Laparoscope-Holding Robot

A Force-driven and Vision-driven Hybrid Control Method of Au...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jin Fang Ling Li Xiaojian Li Hangjie Mo Pengxin Guo Xilin Xiao Yanwei Qu School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education) Hefei University of Technology Hefei China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Laparoscope-holding robots significantly enhance the stability and precision of visualization in minimally invasive surgeries. Most existing robots of this kind depend on visual servo systems and struggle with efficient, rapid adjustments in the field-of-view (FOV), especially when identifying organs and needles outside the FOV. This paper presents a laparoscope-holding robot system capable of employing both vision-driven and force-driven mechanisms for continuous and large-scale FOV adjustments, respectively. The system features an integrated tactile handle, enabling the reception of human-robot interaction forces during surgical navigation. We propose a hybrid control method that leverages both force and vision inputs for laparoscopic FOV adjustments. This approach integrates a virtual wrench, generated from visual information, and an interaction wrench, obtained from the tactile handle, into the robot's dynamic model, which complies with remote center of motion constraints. The interaction wrench's gain is adjusted with the gripping force on the integrated tactile handle, ensuring that unintended movements caused by accidental contacts are prevented, thus safeguarding operational safety. The proposed method eliminates the need to switch control modes, enabling simultaneous visual tracking and tactile interaction guidance. Experimental results demonstrate that the proposed method not only allows for FOV adjustments with surgical instrument guiding but also adapts well to large-scale FOV adjustment tasks.

关键词： Laparoscopes Visualization Tracking Instruments Force Human-robot interaction Switches

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Communication-efficient Distributed Learning for Nash Equilibrium of Aggregative Games over Time-varying Digraphs

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年

作者： Chen, Mingfei Wang, Dong Xu, Xiaopeng Yao, Wenli Zhu, Bingyang Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering China Northwestern Polytechnical University School of Automation Shaanxi Xi'an710129 China

Communication efficiency is a major challenge in learning the Nash equilibrium (NE) of aggregative games in a distributed manner. To address this problem, this paper focuses on designing a communication-efficient algorithm under unbalanced digraphs, where the cost function of each player is affected by its own actions and the average aggregation function. In particular, the considered games have no central node, and no player has direct access to the aggregation function. To estimate the aggregation function, an auxiliary variable is employed to estimate the right Perron eigenvector of the column-stochastic weight matrix, which extends the dynamic average consensus protocol to time-varying digraphs Additionally, players exchange information periodically and perform multi-step local updates with local information between two consecutive communications. By combining the above two strategies with the gradient descent method, a communication-efficient algorithm is proposed and achieves a linear convergence rate. Then the communication period selection method is provided to determine the best trade-off between local updates and information exchange under limited resources. Finally, numerical results demonstrate the effectiveness of the proposed algorithm. © 2020 IEEE.

关键词： Cost functions

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Simulation and Transfer of Physical Image Features Based on Recurrent Generative Adversarial Networks

Simulation and Transfer of Physical Image Features Based on ...

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Chinese Automation Congress (CAC)

作者： Yongxiang Dong Chaochao Qiu Qinghui Pan Feiyue Wu Juncheng Jiang Jie Lian Dong Wang Wei Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Training machine learning models in virtual environments often fails to generalize effectively to real-world applications. The discrepancy between simulated and real environments results in suboptimal performance of the learned models. Various approaches have been proposed to address this “simulation-to-reality gap,” including refining training images within simulations or randomizing virtual environments to narrow the disparity. A CycleGAN model is used to convert simulated images into real ones for correction, but this method remains task-agnostic and does not preserve task-specific information, which can negatively affect task performance. Critical features, particularly those directly related to the task, may be lost during translation, which can compromise task success. To address this issue, conditional information is introduced during the image transformation process to ensure that task-relevant features, such as location data, are retained. This method makes the transformation task-aware rather than task-agnostic. Additionally, skip connections are implemented to mitigate blurring in the generated images. The proposed method has been trained on a custom dataset from a laboratory environment and validated on a robotic arm. This approach significantly improves the accuracy of image conversion tasks and enhances the efficiency of sim-to-real image translation.

关键词： Training Image transformation Translation Refining Laboratories Virtual environments Grasping Machine learning Manipulators Robustness

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Wavelet Function Based Spectral Model Calibration for Measuring Crystallization Solution via ATR-FTIR Spectroscopy 11

Wavelet Function Based Spectral Model Calibration for Measur...

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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Pei, Xiaojing Liu, Tao Liu, Jingxiang Hao, Shoulin Yang, Siwei Dalian University of Technology Ministry of Education Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Dalian116024 China Institute of Advanced Control Technology Dalian University of Technology Dalian116024 China School of Marine Electrical Engineering Dalian Maritime University Dalian116026 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

For measuring the solution concentration of crystallization process by ATR-FTIR spectroscopy, this paper proposes an improved spectral model calibration method to guarantee in-situ measurement accuracy, based on wavelet function regression. The spectral model structure is composed of wavelet basis functions, which could address the nonlinear properties and high-dimensional problem of infrared spectral variables. Moreover, the mean centralization strategy is taken to reduce the influence from measurement noise. In addition, a comparative study on measuring the solution concentration of the L-glutamic acid (LGA) crystallization process is conducted in terms of using different modeling methods and spectral variables. It is found that the wavelet function regression with all spectral variables could obtain good measurement accuracy compared to the traditional partial least-squares (PLS) method. Experimental results well demonstrate the measurement accuracy of the proposed spectral calibration method. © 2022 IEEE.

关键词： Fourier transform infrared spectroscopy

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Reconstructing cell lineage trees with genomic barcoding:approaches and applications

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Journal of Genetics and Genomics 2024年第1期51卷 35-47页

作者： Zizhang Li Wenjing Yang Peng Wu Yuyan Shan Xiaoyu Zhang Feng Chen Junnan Yang Jian-Rong Yang Advanced Medical Technology Center The First Affiliated HospitalZhongshan School of MedicineSun Yat-sen UniversityGuangzhouGuangdong 510080China Department of Genetics and Biomedical Informatics Zhongshan School of MedicineSun Yat-sen UniversityGuangzhouGuangdong 510080China Key Laboratory of Tropical Disease Control Ministry of EducationSun Yat-sen UniversityGuangzhouGuangdong 510080China

In multicellular organisms,developmental history of cell divisions and functional annotation of terminal cells can be organized into a cell lineage tree(CLT).The reconstruction of the CLT has long been a major goal in developmental biology and other related *** technological advancements,especially those in editable genomic barcodes and single-cell high-throughput sequencing,have sparked a new wave of experimental methods for reconstructing *** we review the existing experimental approaches to the reconstruction of CLT,which are broadly categorized as either image-based or DNA barcode-based *** addition,we present a summary of the related literature based on the biological insight pro-vided by the obtained ***,we discuss the challenges that will arise as more and better CLT data become available in the near *** barcoding-based CLT reconstructions and analyses,due to their wide applicability and high scalability,offer the potential for novel biological discoveries,especially those related to general and systemic properties of the developmental process.

关键词： Cell lineage tree Developmental regulation Biotechnology Computational biology

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Batch process Monitoring with Two-dimensional LSTM-Variational Auto-encoder

Batch Process Monitoring with Two-dimensional LSTM-Variation...

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第42届中国控制会议

作者： Zhong Liu Xuyang Lou Jinlin Zhu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Jiangnan University School of Food Science and Technology Jiangnan University

Batch process monitoring is crucial in production loss prevention and process safety promotion. However, the two-dimensional nonlinear dynamics in the batch process make the monitoring cumbersome. This paper proposes a novel dynamic deep model called two-dimensional LSTM variational auto-encoder(2DLSTM-VAE). Structurally, our model constructs with LSTM encoded under the conditional variational Bayes framework, which can cope with the nonlinear dynamics from two dimensions. Afterwards, a systematic fault detection framework is defined under the latent and residual domains to account for each running batch along with those run-to-run variations so as to reflect the process variability in the two-way monitoring aspects. Finally, a deep reconstruction-based contribution(DRBC) diagram is further developed to investigate root causes. For the case study, the validity of the 2DLSTM-VAE model is demonstrated in the penicillin fermentation process, and the results show that compared with other methods, the proposed deep model has better performance on fault detection and diagnosis.

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