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Catalog of Dynamical System Models with Semantic Metadata

PAMM 2023年第2期23卷

作者： Julius Fiedler Carsten Knoll Institute of Control Theory TUD Dresden University of Technology Dresden Germany Chair of Fundamentals of Electrical Engineering TUD Dresden University of Technology Dresden Germany

This contribution presents the concept and implementation of a catalog (i.e., a structured collection) of dynamical system models, relevant to control theory. The key features of the catalog are: (a) a combination of human-readable model documentation with executable code; (b) semantic metadata for each model plus a web platform to provide SPARQL search interface; and (c) model data and supporting software based on open source repositories and open for extension and improvement.

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Binding of the three-hadron DD*K system from the lattice effective field theory

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Physical Review D 2025年第3期111卷 036002-036002页

作者： Zhenyu Zhang Xin-Yue Hu Guangzhao He Jun Liu Jia-Ai Shi Bing-Nan Lu Qian Wang Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear Science Southern Nuclear Science Computing Center South China Normal University Guangzhou 510006 China Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum Matter South China Normal University Guangzhou 510006 China Graduate School of China Academy of Engineering Physics Beijing 100193 China Southern Center for Nuclear-Science Theory (SCNT) Institute of Modern Physics Chinese Academy of Sciences Huizhou 516000 Guangdong Province China

We employ the nuclear lattice effective field theory (NLEFT), an efficient tool for nuclear ab initio calculations, to solve the asymmetric multihadron systems. We take the DD*K three-body system as an illustration to demonstrate the capability of the method. Here the two-body chiral interactions between D, D*, and K are regulated with a soft lattice regulator and calibrated with the binding energies of the Tcc+, Ds0*(2317), and Ds1(2460) molecular states. We then calculate the three-body binding energy using the NLEFT and analyze the systematic uncertainties due to the finite volume effects, the sliding cutoff, and the leading-order three-body forces. Even when the three-body interaction is repulsive (even as large as the infinite repulsive interaction), the three-body system has a bound state unambiguously with binding energy no larger than the Ds1(2460)D threshold. To check the renormalization group invariance of our framework, we extract the first excited state. We find that when the ground state is fixed, the first excited states with various cutoffs coincide with each other when the cubic size goes larger. In addition, the standard angular momentum and parity projection technique is implemented for the quantum numbers of the ground and excited states. We find that both of them are S-wave states with quantum number JP=1−. Because the three-body state contains two charm quarks, it is easier to be detected in the Large Hadron Collider.

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Consistent Kalman flters for nonlinear uncertain systems over sensor networks

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control theory and Technology 2020年第4期18卷 399-408页

作者： Xingkang He Wenchao Xue Haitao Fang Xiaoming Hu Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology10044 StockholmSweden LSC NCMISAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Optimization and Systems Theory Department of MathematicsKTH Royal Institute of Technology10044 StockholmSweden

In this paper,we study how to design filters for nonlinear uncertain systems over sensor *** intoduce two Kalmantype nonlinear fitrs in centralied and dstrbute ***,the tuning method for the parameters of the filteres is established to ensure the consistency,i.e..the mean square error is upper bounded by a known parameter matrix at each *** apply the consistent fiters to the track to-track association analysis of multi targets with uncertain dynamics.A novel track to-track asocaion algoritm is proposed to idenify whether two tracks are from the same *** is proven that the resulting probability of *** is lower than the desired *** simulations on *** track association are given to show the ffetives of the methods.

关键词： Kalman fiter Consistencey Distributed fiter Track-to-rack asociation

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Design of parallel compensator and stabilizing controller to mitigate non-minimum phase behaviour of the Czochralski Process

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IFAC-PapersOnLine 2020年第2期53卷 11710-11715页

作者： Halima Zahra Bukhari Morten Hovd Muhammad Faisal Aftab Jan Winkler Department of Engineering Cybernetics NTNU Trondheim Norway Department of Engineering Sciences University of Agder Norway Institute of Control Theory Faculty of Electrical & Computer Engineering TU Dresden Germany

This paper addresses the design of a parallel compensator and a stabilizing controller for the simplified crystal growth dynamics of the Czochralski (CZ) process, i.e., the process for the production of monocrystalline silicon ingots of uniform diameter. The diameter control of the produced ingots is achieved by a CCD camera measurement used to sense the radius of the boundary between the base of the growing crystal and the surrounding glowing meniscus — a raised melt surface connecting the crystal ingot with the flatter melt surface. Due to the intrinsic nature of the process, the bright ring radius measurement signal exhibits a non-minimum phase behaviour. A combination of the parallel compensator and a stabilizing controller is designed, such that the former provides for the mitigation of non-minimum phase behaviour, while the latter combined with the formal yields a suitable closed-loop performance.

关键词： Czochralski process bright ring radius measurement parallel compensator non-minimum phase ray tracing interface dynamics

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Steady state behavior of the free recall dynamics of working memory

arXiv

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arXiv 2022年

作者： Li, Tianhao Liu, Zhixin Liu, Lizheng Hu, Xiaoming Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100190 China Academy for Engineering and Technology Fudan University Shanghai200433 China Optimization and Systems Theory KTH Royal Institute of Technology Stockholm10044 Sweden

This paper studies a dynamical system that models the free recall dynamics of working memory. This model is a modular neural network with n modules, named hypercolumns, and each module consists of m minicolumns. Under mild conditions on the connection weights between minicolumns, we investigate the long-term evolution behavior of the model, namely the existence and stability of equilibriums and limit cycles. We also give a critical value in which Hopf bifurcation happens. Finally, we give a sufficient condition under which this model has a globally asymptotically stable equilibrium with synchronized minicolumn states in each hypercolumn, which implies that in this case recalling is impossible. Numerical simulations are provided to illustrate our theoretical results. A numerical example we give suggests that patterns can be stored in not only equilibriums and limit cycles, but also strange attractors (or chaos). Copyright © 2022, The Authors. All rights reserved.

关键词： Asymptotic stability

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Prediction Model of User Purchase Behavior Based on Machine Learning 17

Prediction Model of User Purchase Behavior Based on Machine ...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Zhai, Xiang Shi, Peng Xu, Liang Wang, Yalong Chen, Xi Tianjin University of Technology Binshui Xidao 391 Tianjin Key Laboratory for Control Theory Applications in Complicated Systems School of Electrical and Electronic Engineering Tianjin China Luoyang Institute of Electro-Optical Equipment Avic Luoyang471000 China

ISBN: (纸本)9781728164151

In recent years, with the continuous popularity of the Internet, the number of online shopping users in my country has reached 639 million, which contains huge commercial value. In order to maintain the prosperity, diversity and order of merchants, and fully meet consumers' one-stop shopping needs, it is necessary to analyze and predict user purchase behaviors more accurately. This article uses the interaction between users and products within a certain period of time provided by *** to predict whether users will place orders in designated categories and shops in the next week. First of all, we aim at the problem that the original features are not strongly related, and use feature fusion to construct strong features. For high-dimensional systems that are slow to calculate and prone to overfitting, we use random forests to filter features, reducing the complexity of the model. Finally, a fusion algorithm based on XGBoost and LightGBM is proposed to predict the purchase behavior of users, and the prediction effects of random forest and GBDT algorithm are compared at the same time. The results show that the fusion model has the best prediction effect, and can help merchants more accurately conduct marketing activities to potential customers based on the prediction results. © 2020 IEEE.

关键词： Forecasting

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The Impact of Element Spatial Arrangement on Ultrasound Tomography: Experimental Results

The Impact of Element Spatial Arrangement on Ultrasound Tomo...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Yu Yuan Yue Zhao Yi Shen Yang Xiao Yuemin Zhu Jing Jin Naizhang Feng Control Theory and Engineering Harbin Institute of Technology Harbin P.R. China Control Theory and Engineering Harbin Institute of Technology (Shenzhen) Shenzhen P.R. China INSA Lyon CNRS Inserm Univ Lyon Lyon France

ISBN: (数字)9781728144801

ISBN: (纸本)9781728144818

Breast cancer has become one of the most common and lethal cancers in women worldwide. Ultrasound tomography (UST) is supposed to be an imaging method for early diagnosis of breast cancer. In the implementation of UST, operators usually need to compromise between the image quality and the complexity of scanning. In order to explore the relationship between them, a preliminary UST imaging system is designed and introduced in this paper. It uses two co-planar 128-element piezoelectric ultrasonic transducers as transmitter and receiver respectively, each of which can rotate freely in the horizontal plane. Based on this prototype, a series of experiments with different scanning patterns are designed, the corresponding signal completeness are calculated, and the imaging results are compared.

关键词： Imaging Transducers Ultrasonic imaging Image reconstruction Acoustics Tomography Receivers

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A Dueling-Double-Deep Q-Network controller for Magnetic Levitation Ball System

A Dueling-Double-Deep Q-Network Controller for Magnetic Levi...

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第三十九届中国控制会议

作者： Yefeng Yang Xiaojun Ban Xianlin Huang Chenghao Shan Center for Control Theory and Guidance Technology Harbin Institute of Technology Institute of Marine Navigation Technology Harbin Engineering University

Deep reinforcement learning technique has attracted extensive attention in the field of control with the rapid development of artifical intelligence. Model-free control methods perform more effcient than traditional model-based control method for complex nonlinear system since they don’t require accurate models. In this study, by using the Dueling-Double-DQN（Dueling-DDQN, 3-DQN） algorithm, a self-learning controller is developed for the magnetic levitation ball system. The numerical simulation demonstrates the effectiveness of our controller. Moreover, we compare the above controller with the DQN-based self-learning controller. Numerical simulation shows that the attraction domain of the Dueling-DDQN controller is larger that the latter.

关键词： Reinforcement learning Magnetic levitation ball system Dueling-Double-DQN Model-free control

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A distributed optimization algorithm for Nash bargaining in multi-agent systems ⁎

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IFAC-PapersOnLine 2020年第2期53卷 2684-2689页

作者： Andrea Camisa Philipp N. Köhler Matthias A. Müller Giuseppe Notarstefano Frank Allgöwer Department of Electrical Electronic and Information Engineering Alma Mater Studiorum Università di Bologna Bologna Italy Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Institute of Automatic Control Leibniz University Hannover Hannover Germany

In this paper, we consider a multi-objective optimization problem over networks in which agents aim to maximize their own objective function, while satisfying both local and coupling constraints. This set up includes, e.g., the computation of optimal steady states in multi-agent control systems. Since fairness is a key feature required for the solution, we resort to Cooperative Game theory and search for the Nash bargaining solution among all the efficient (or Pareto optimal) points of a bargaining game. We propose a negotiation mechanism among the agents to compute such a solution in a distributed way. The problem is reformulated as the maximization of a properly weighted sum of the objective functions. The proposed algorithm is then a two step procedure in which local estimates of the Nash bargaining weights are updated online and existing distributed optimization algorithms are applied. The proposed method is formally analyzed for a particular case, while numerical simulations are provided to corroborate the theoretical findings and to demonstrate its efficacy

关键词： Cooperative game theory Distributed optimization Multi-Objective optimization Nash bargaining Distributed model predictive control Network games

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Knowledge-aware Graph Transformer for Pedestrian Trajectory Prediction

arXiv

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arXiv 2024年

作者： Liu, Yu Zhang, Yuexin Li, Kunming Qiao, Yongliang Worrall, Stewart Li, You-Fu Kong, He Shenzhen518055 China Department of Mechanical Engineering City University of Hong Kong Hong Kong School of Automation Guangdong Polytechnic Normal University Guangzhou510665 China Australian Centre for Field Robotics The University of Sydney NSW2006 Australia Australian Institute for Machine Learning The University of Adelaide SA5005 Australia Shenzhen Key Laboratory of Control Theory and Intelligent Systems SUSTech Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities SUSTech Shenzhen518055 China

Predicting pedestrian motion trajectories is crucial for path planning and motion control of autonomous vehicles. Accurately forecasting crowd trajectories is challenging due to the uncertain nature of human motions in different environments. For training, recent deep learning-based prediction approaches mainly utilize information like trajectory history and interactions between pedestrians, among others. This can limit the prediction performance across various scenarios since the discrepancies between training datasets have not been properly incorporated. To overcome this limitation, this paper proposes a graph transformer structure to improve prediction performance, capturing the differences between the various sites and scenarios contained in the datasets. In particular, a self-attention mechanism and a domain adaption module have been designed to improve the generalization ability of the model. Moreover, an additional metric considering crossdataset sequences is introduced for training and performance evaluation purposes. The proposed framework is validated and compared against existing methods using popular public datasets, i.e., ETH and UCY. Experimental results demonstrate the improved performance of our proposed scheme. © 2024, CC BY.

关键词： Trajectories

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