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arXiv 2024年

作者： Jung, Roland Santoro, Luca Brunelli, Davide Fontanelli, Daniele Weiss, Stephan The Department of Smart Systems Technologies The Control of Networked Systems Group University of Klagenfurt Austria The Department of Industrial Engineering University of Trento Italy

This paper introduces a generic filter-based state estimation framework that supports two state-decoupling strategies based on cross-covariance factorization. These strategies reduce the computational complexity and inherently support true modularity - a perquisite for handling and processing meshed range measurements among a time-varying set of devices. In order to utilize these measurements in the estimation framework, positions of newly detected stationary devices (anchors) and the pairwise biases between the ranging devices are required. In this work an autonomous calibration procedure for new anchors is presented, that utilizes range measurements from multiple tags as well as already known anchors. To improve the robustness, an outlier rejection method is introduced. After the calibration is performed, the sensor fusion framework obtains initial beliefs of the anchor positions and dictionaries of pairwise biases, in order to fuse range measurements obtained from new anchors tightly-coupled. The effectiveness of the filter and calibration framework has been validated through evaluations on a recorded dataset and real-world experiments. Copyright © 2024, The Authors. All rights reserved.

关键词： Inertial navigation systems

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On the relationship between control barrier functions and projected dynamical systems

arXiv

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arXiv 2023年

作者： Delimpaltadakis, Giannis Heemels, W.P.M.H. The Control Systems Technology Group Mechanical Engineering Eindhoven University of Technology Netherlands

In this paper, we study the relationship between systems controlled via control Barrier Function (CBF) approaches and a class of discontinuous dynamical systems, called Projected Dynamical systems (PDSs). In particular, under appropriate assumptions, we show that the vector field of CBF-controlled systems is a Krasovskii-like perturbation of the set-valued map of a differential inclusion, that abstracts PDSs. This result provides a novel perspective to analyze and design CBF-based controllers. Specifically, we show how, in certain cases, it can be employed for designing CBF-based controllers that, while imposing safety, preserve asymptotic stability and do not introduce undesired equilibria or limit cycles. Finally, we briefly discuss about how it enables continuous implementations of certain projection-based controllers, that are gaining increasing popularity. Copyright © 2023, The Authors. All rights reserved.

关键词： controllers

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Reference Model based Data-driven control of Power Amplifiers for High-precision Motion systems

Reference Model based Data-driven Control of Power Amplifier...

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control Technology and Applications (CCTA),

作者： Duo Xu Mihai-Serban Popescu Mircea Lazar Department of Electrical Engineering Control Systems Group Eindhoven University of Technology The Netherlands

Motivated by the increasing requirements in positioning precision for lithography applications, this paper analyzes how the position error in a high-precision motion system is affected by the response of the controlled power amplifier that drives the motor. Based on the analysis, guidelines for designing a reference model in continuous or discrete time that satisfies certain requirements that would decrease the overall position error are presented. Then, a data-driven control method, namely Virtual Reference Feedback Tuning (VRFT), is employed to directly synthesize both feedback and feedforward controllers based on the designed reference model. The position error of the motion system with the data-driven controlled power amplifier is compared to the case when classical industrial controllers are employed in the control of the amplifier. If adequate reference models are designed, the VRFT-controlled power amplifier can significantly decrease the position error such that it is close to the ideal position error. All of the presented results are based on simulations.

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Local Identification in Dynamic Networks using a Multi-Step Least Squares Method

Local Identification in Dynamic Networks using a Multi-Step ...

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IEEE Conference on Decision and control

作者： Stefanie J.M. Fonken Karthik R. Ramaswamy Paul M.J. Van Den Hof Department of Electrical Engineering Control Systems Group Eindhoven University of Technology The Netherlands

For identification of a single module in a linear dynamic network with correlated disturbances different meth-ods are available in a prediction error setting. While indirect methods fully rely on the presence of a sufficient number of external excitation signals for achieving data-informativity, the local direct method with a MIMO predictor model can exploit also non-measured disturbance signals for data-informativity. However, a simple two-node example shows that this local direct method can also be conservative in terms of the number of ex-ternal excitation signals that is required. Inspired by a recently introduced multi-step method for full network identification, we present a multi-step least squares method for single module identification. In a first indirect step a model is estimated that is used to reconstruct the innovation on a set of output signals, which in a second step is used to directly estimate the module dynamics with a MISO predictor model. The resulting path-based conditions for data-informativity show that the multi-step method requires a smaller number of excitation signals for data-informativity than the local direct method.

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Fast model predictive control of power amplifiers for nanometer precision motion systems

Fast model predictive control of power amplifiers for nanome...

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European control Conference (ECC)

作者： Duo Xu Mircea Lazar Department of Electrical Engineering Control Systems Group Eindhoven University of Technology The Netherlands

This paper deals with the design of a fast MPC algorithm for the current control of a power amplifier utilized for nanometer precision positioning systems within lithography machines. In order to achieve nanometer precision positioning, the internal power amplifier must accurately track a current reference in a very short time (tens of microseconds). Classical industrial control solutions based on transfer functions do not take duty-cycle limits into account and suffer from limited bandwidth, which in turn limits the achievable positioning precision. We design a fast gradient based MPC algorithm that can accurately track the dynamic current reference while satisfying constraints. Simulations show that the MPC-controlled amplifier results in at least 2x better nanometer positioning precision for specific metrics employed in the lithography industry, compared to an industrial loop-shaping controller and an LQR controller.

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Modular Meshed Ultra-Wideband Aided Inertial Navigation with Robust Anchor Calibration

Modular Meshed Ultra-Wideband Aided Inertial Navigation with...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Roland Jung Luca Santoro Davide Brunelli Daniele Fontanelli Stephan Weiss Department of Smart Systems Technologies Control of Networked Systems Group University of Klagenfurt Austria Department of Industrial Engineering University of Trento Italy

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper introduces a generic filter-based state estimation framework that supports two state-decoupling strategies based on cross-covariance factorization. These strategies reduce the computational complexity and inherently support true modularity – a perquisite for handling and processing meshed range measurements among a time-varying set of devices. In order to utilize these measurements in the estimation framework, positions of newly detected stationary devices (anchors) and the pairwise biases between the ranging devices are required. In this work an autonomous calibration procedure for new anchors is presented, that utilizes range measurements from multiple tags as well as already known anchors. To improve the robustness, an outlier rejection method is introduced. After the calibration is performed, the sensor fusion framework obtains initial beliefs of the anchor positions and dictionaries of pairwise biases, in order to fuse range measurements obtained from new anchors tightly-coupled. The effectiveness of the filter and calibration framework has been validated through evaluations on a recorded dataset and real-world experiments.

关键词： Performance evaluation Protocols Position measurement Sensor fusion Distance measurement Robustness Real-time systems Calibration State estimation Ultra wideband technology

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Integration of a multi-rate electron density profile observer in the plasma control system of TCV 49

Integration of a multi-rate electron density profile observe...

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49th EPS Conference on Plasma Physics, EPS 2023

作者： Pastore, F. Felici, F. Sauter, O. Bosman, T.O.S.J. Galperti, C. Vincent, B. Pau, A. Poels, Y. Ravensbergen, T. Vu, N.M.T. Lausanne Switzerland DIFFER - Dutch Institute for Fundamental Energy Research Energy Systems and Control Group Eindhoven Netherlands Eindhoven University of Technology Dept. of Mechanical Engineering Control Systems Technology Group Eindhoven Netherlands Eindhoven University of Technology Dept. of Mathematics and Computer Science Data Mining Group Eindhoven Netherlands ITER Organization Route de Vinon-sur-Verdon St. Paul Lez Durance13067 Cedex France

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Consensus-based distributed model predictive control applied to modular multilevel converters

Consensus-based distributed model predictive control applied...

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control Technology and Applications (CCTA),

作者： Victor Daniel Reyes Dreke Shiqi Duan Mircea Lazar Department of Electrical Engineering Control Systems Group Eindhoven University of Technology The Netherlands

Modular multilevel converters (MMCs) have the potential to improve the performance of high- and medium-power applications, such as renewable energy generation and fast charging stations. The functioning of MMCs relies on their ability to balance capacitor voltages across all modules. Motivated by the capacitor voltage balancing (CVB) problem, this paper studies consensus-based distributed model predictive control (DMPC) schemes. As a result, we propose an alternative cost function that enables output synchronization of linear systems and, consequently, solves the CVB problem. The advantages of the proposed method are demonstrated by proving its stability properties and comparing its computational time and performance with existing DMPCs. Simulation results for a benchmark multi-agent system example from the literature and an MMC AC/DC topology demonstrate the effectiveness of the developed consensus DMPC.

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Steps Toward Industry 5.0:Building“6S”Parallel Industries With Cyber-Physical-Social Intelligence

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1692-1703页

作者： Xingxia Wang Jing Yang Yutong Wang Qinghai Miao Fei-Yue Wang Aijun Zhao Jian-Ling Deng Lingxi Li Xiaoxiang Na Ljubo Vlacic School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China North Automatic Control Technology Institute Taiyuan 030006China China Huaneng Group Co. Ltd.Beijing 100031China Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis(IUPUI)IndianapolisIN 46202 USA Department of Engineering University of CambridgeCambridgeCB21PZUK School of Engineering and Built Environment Griffith UniversityGold CoastQLD 4222Australia

Very recently,intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers,entrepreneurs,and policymakers from various sectors around the ***,there is no consensus on why and what is Industry 5.0 *** this paper,we define Industry 5.0from its philosophical and historical origin and evolution,emphasize its new thinking on virtual-real duality and human-machine interaction,and introduce its new theory and technology based on parallel intelligence(PI),artificial societies,computational experiments,and parallel execution(the ACP method),and cyber-physical-social systems(CPSS).Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future *** believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart *** are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces,S ecure in cyberspaces,Sustainable in ecology,Sensitive in individual privacy and rights,Service for all,and Smartness of all.

关键词： ACP artificial intelligence CPS CPSS Industry 4.0 Industry 5.0 parallel industries parallel intelligence

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Learning Flow Functions from Data with Applications to Nonlinear Oscillators

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IFAC-PapersOnLine 2023年第2期56卷 4088-4093页

作者： Miguel Aguiar Amritam Das Karl H. Johansson Division of Decision and Control Systems and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Control Systems Group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands

We describe a recurrent neural network (RNN) based architecture to learn the flow function of a causal, time-invariant and continuous-time control system from trajectory data. By restricting the class of control inputs to piecewise constant functions, we show that learning the flow function is equivalent to learning the input-to-state map of a discrete-time dynamical system. This motivates the use of an RNN together with encoder and decoder networks which map the state of the system to the hidden state of the RNN and back. We show that the proposed architecture is able to approximate the flow function by exploiting the system's causality and time-invariance. The output of the learned flow function model can be queried at any time instant. We experimentally validate the proposed method using models of the Van der Pol and FitzHugh-Nagumo oscillators. In both cases, the results demonstrate that the architecture is able to closely reproduce the trajectories of these two systems. For the Van der Pol oscillator, we further show that the trained model generalises to the system's response with a prolonged prediction time horizon as well as control inputs outside the training distribution. For the FitzHugh-Nagumo oscillator, we show that the model accurately captures the input-dependent phenomena of excitability.

关键词： Oscillator Learning Recurrent Neural Network Excitability

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