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第41届中国控制会议

作者： Yue Ju Tianshi Chen Biqiang Mu Lennart Ljung School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of Sciences Division of Automatic Control Department of Electrical EngineeringLink?ping University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Asymptotic theory for the regularized system identification has received increasing interests in recent *** this paper,for the finite impulse response(FIR) model and filtered white noise inputs,we show the convergence in distribution of the Stein's unbiased risk estimator(SURE) based hyper-parameter estimator and find factors that influence its convergence *** particular,we consider the ridge regression case to obtain closed-form expressions of the limit of the regression matrix and the variance of the limiting distribution of the SURE based hyper-parameter estimator,and then demonstrate their relation numerically.

关键词： Asymptotic theory Stein's unbiased risk estimator Hyper-parameter estimator Regularized system identification

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing 26

On the Approximation of the Quotient of Two Gaussian Densiti...

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26th International Conference on Information Fusion, FUSION 2023

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Xue, Yanbo University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Career Science Lab Beijing China

ISBN: (纸本)9798890344854

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target. © 2023 International Society of Information Fusion.

关键词： Cost functions

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Fuzzy Logic control in Metal Additive Manufacturing: A Literature Review and Case Study

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IFAC-PapersOnLine 2022年第21期55卷 37-42页

作者： Taha Al-Saadi J. Anthony Rossiter George Panoutsos Department of Automatic Control and System Engineering University of Sheffield Mapping Street S1 3JD UK

Since the development of the Fuzzy Logic theory by Zadah (1965), motivated by the human-level understanding of systems for the development of computational and mathematical frameworks, it has become an active research field for a broad spectrum of research in academia and the industry, from systems modelling to systems monitoring and control. In this research, the authors intend to highlight the use of Fuzzy Logic theory in metal additive manufacturing processes. The modelling of such processes has a lot of uncertainties due to the large underlying physics during the operation, which makes the Fuzzy Logic controller a promising tool to deal with such a process. This work will provide a survey of the previous efforts and a case study to illustrate the approach's effectiveness in such a complex manufacturing technique.

关键词： metallic additive manufacturing laser powder bed fusion control fuzzy logic

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An INS Fault Diagnosis Method Based on State Chi-Square Test and Optimized GA-BP Neural Network

An INS Fault Diagnosis Method Based on State Chi-Square Test...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Ji, Yinglin Wu, Falin Zhang, Yachong Liu, Yushuang Zhang, Zhidong SNARS Laboratory School of Instrumentation and Optoelectronic Engineering Beihang University Beijing100191 China Xi’an Flight Automatic Control Research Institute Xi’an710076 China Beijing System Design Institute of Electro-mechanic Engineering Beijing100854 China

ISBN: (纸本)9789811581540

The failure of the INS will directly lead to navigation errors in an INS/GNSS integrated system. This paper presents an INS fault detection and diagnosis method using state Chi-square test (SCST)and optimized genetic algorithm and Back-Propagation neural network(GA-BP). Firstly, SCST is used to detect fault and the results of SCST is extracted as the feature data of fault diagnosis. Secondly, the selection strategy and calculation method of crossover and mutation probability are optimized to improve the performance of genetic algorithm. Then the optimized genetic algorithm is used for global search to optimally acquire the initial weight and the threshold of the BP neural network. Finally, two optimized GA-BP neural networks are applied to locate the fault and obtain the magnitude and type. The results of the simulation demonstrate that the method is able to diagnose the fault location, magnitude and type with high accuracy. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Inertial navigation systems

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Design and Implementation of Dynamic Reconfiguration Based on Heterogeneous Arrow control Platform 15

Design and Implementation of Dynamic Reconfiguration Based o...

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15th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2021

作者： Tao, Ran Xiang, Gang Luo, Yue Tian, Kun Li, Hui Wang, Zhaolei Beijing Aerospace Automatic Control Research Institute Beijing China Beijing Inst. Of Electronic System Engineering Beijing China

ISBN: (纸本)9781665444910

Traditional rocket control computing platform use hardware redundancy more ways to promote the reliability, the same hardware redundancy of common cause failure, unable to cope with complex environment against the shortcomings, is proposed based on heterogeneous architecture arrows control platform, by using SOPC, FPGA and DSP three core components to build a new generation of control computing platform, has high reliability, strong adaptability to environment, etc. With SOPC as the core, the heterogeneous platform completes data transmission through high-speed serial transmission, supports dynamic logical reconstruction, and utilizes dynamic reconstruction technology to realize self-recovery under abnormal state. In this paper, the platform architecture, data transmission and synchronization methods, dynamic reconstruction strategy and control methods are described in detail. Finally, the correctness of the platform design is verified by experiments and simulations. © 2021 IEEE.

关键词： Dynamic models

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Graph-based semantic planning for adaptive human-robot-collaboration in assemble-to-order scenarios

Graph-based semantic planning for adaptive human-robot-colla...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Ruidong Ma Jingyu Chen John Oyekan Department of Automatic Control and System Engineering University of Sheffield Sheffield United Kingdom Department of Computer Science University of York York United Kingdom

Assemble-to-Order (ATO) has become a popular production strategy for the increasing demand for mass-customized manufacturing. In order to facilitate a flexible and automated Human-Robot-Collaboration system for ATO, we propose a Learning from Demonstration (LfD) framework based on 2D videos in this paper. We initially combine temporal hand motions with spatial hand-object interactions to detect assembly actions. Therefore, an assembly graph can be constructed using classified action sequences. Compared to previous studies on task planning for robots, our graph-based semantic planner can directly learn the demonstrated task structure and thus produce more detailed assistive robot actions for more effective collaboration. We validate our approach by applying it to a real-world ATO problem. The results demonstrated that our proposed system can produce actions adaptively in response to varying human action sequences, as well as guide human assembly when the robot is not involved. Our approach also shows generalizability to unseen human action sequences.

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Preventing Frequency Instability Using Large-Scale Photovoltaic Resources

Preventing Frequency Instability Using Large-Scale Photovolt...

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Technology and Energy Management (ICTEM), International Conference on

作者： Siavash Yari Hamid Khoshkhoo Kumars Rouzbehi S. M. Ale Emran Faculty of Electrical Engineering Sahand University of Technology Sahand Iran Department of System Engineering and Automatic Control University of Seville Seville Spain Faculty of Engineering University of Quebec at Chicoutimi (UQAC)

Various control methods have been presented to prevent the occurrence of instability in power systems, among which, it seems that methods based on the special protection system (SPS) are more effective and efficient than other ones. In this article, a SPS using the capabilities of large-scale photovoltaic power plants (LSPVPPs) is presented to prevent frequency increase and instability in power systems. According to the presented algorithm, when frequency increases, the proposed SPS uses the ability of photovoltaic power plants to quickly change their generation powers based on the operating point and frequency changes to prevent frequency instability. To confirm the proposal, LSPVPPs along with their controllers are modeled in the DSL environment of DIgSILENT PowerFactory software. The proposed SPS is implemented and tested on the IEEE 39-bus test system and the results of dynamic simulations show that this SPS prevents frequency instability in different conditions by taking timely measures.

关键词： Photovoltaic systems Time-frequency analysis Power system dynamics Software algorithms Power system stability Stability analysis Software

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Derivative-Free Data-Driven control of Continuous-Time Linear Time-Invariant systems

arXiv

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arXiv 2024年

作者： Bosso, Alessandro Borghesi, Marco Iannelli, Andrea Notarstefano, Giuseppe Teel, Andrew R. Department of Electrical Electronic and Information Engineering University of Bologna Italy Institute for System Theory and Automatic Control University of Stuttgart Germany Department of Electrical and Computer Engineering University of California Santa BarbaraCA United States

This paper develops a data-driven stabilization method for continuous-time linear time-invariant systems with theoretical guarantees and no need for signal derivatives. The framework, based on linear matrix inequalities (LMIs), is illustrated in the state-feedback and single-input single-output output-feedback scenarios. Similar to discrete-time approaches, we rely solely on input and state/output measurements. To avoid differentiation, we employ low-pass filters of the available signals that, rather than approximating the derivatives, reconstruct a non-minimal realization of the plant. With access to the filter states and their derivatives, we can solve LMIs derived from sample batches of the available signals to compute a dynamic controller that stabilizes the plant. The effectiveness of the framework is showcased through numerical examples. © 2024, CC BY.

关键词： Continuous time systems

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Free-form Grid Structure Form Finding based on Machine Learning and Multi-objective Optimisation

arXiv

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arXiv 2024年

作者： Meng, Yiping Sun, Yiming School of Computing Engineering & Digital Technologies Teesside University Tees Valley MiddlesbroughTS1 3BX United Kingdom Department of Automatic Control and System Engineering University of Sheffield United Kingdom

Free-form structural forms are widely used to design spatial structures for their irregular spatial morphology. Current free-form form-finding methods cannot adequately meet the material properties, structural requirements or construction conditions, which brings the deviation between the initial 3D geometric design model and the constructed free-form structure. Thus, the main focus of this paper is to improve the rationality of free-form morphology considering multiple objectives in line with the characteristics and constraints of material. In this paper, glued laminated timber is selected as a case. Firstly, machine learning is adopted based on the predictive capability. By selecting a free-form timber grid structure and following the principles of NURBS, the free-form structure is simplified into free-form curves. The transformer is selected to train and predict the curvatures of the curves considering the material characteristics. After predicting the curvatures, the curves are transformed into vectors consisting of control points, weights, and knot vectors. To ensure the constructability and robustness of the structure, minimising the mass of the structure, stress and strain energy are the optimisation objectives. Two parameters (weight and the z-coordinate of the control points) of the free-from morphology are extracted as the variables of the free-form morphology to conduct the optimisation. The evaluation algorithm was selected as the optimal tool due to its capability to optimise multiple parameters. While optimising the two variables, the mechanical performance evaluation indexes such as the maximum displacement in the z-direction are demonstrated in the 60th step. The optimisation results for structure mass, stress and strain energy after 60 steps show the tendency of oscillation convergence, which indicates the efficiency of the proposal multi-objective optimisation. © 2024, CC BY-NC-ND.

关键词： Morphology

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Unsupervised Learning-Based Methodology for Detection of Postural Anomalies in Wheelchair Users

Unsupervised Learning-Based Methodology for Detection of Pos...

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IEEE International Conference on systems, Man and Cybernetics

作者： Patrick Vermander Aitziber Mancisidor Giancarlo Fortino Itziar Cabanes Raffaele Gravina Department of Automatic Control and System Engineering University of the Basque Country (UPV/EHU) Bilbao Spain Department of Informatics Modeling Electronics and Systems engineering University of Calabria (UNICAL) Rende Italy

Postural monitoring in wheelchair users is a topic of growing interest. The detection of changes in the sitting patterns of these patients may serve to detect changes in their functional status and be able to adapt rehabilitation early. For this reason, this paper presents a methodology for the detection of specific postural anomalies that, unlike previous works, adopts unsupervised learning. The proposed methodology involves data dimensionality reduction using Principal Component Analysis, and the application of K-means clustering to group different normal posture states. The anomalies are detected using a threshold approach, where data points that fall outside a certain threshold are considered as anomalies. The results show that the methodology is effective in identifying anomalies with a high degree of accuracy (around 90%).

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