liu.seSearch for publications in DiVA
Change search
Refine search result
7374757677 3751 - 3800 of 3807
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 3751.
    Yu, Chengpu
    et al.
    Beijing Inst Technol, Peoples R China.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Verhaegen, Michel
    Delft Univ Technol, Netherlands.
    Identification of structured state-space models2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 90, p. 54-61Article in journal (Refereed)
    Abstract [en]

    Identification of structured state-space (gray-box) model is popular for modeling physical and network systems. Due to the non-convex nature of the gray-box identification problem, good initial parameter estimates are crucial for successful applications. In this paper, the non-convex gray-box identification problem is reformulated as a structured low-rank matrix factorization problem by exploiting the rank and structured properties of a block Hankel matrix constructed by the system impulse response. To address the low-rank optimization problem, it is first transformed into a difference-of-convex (DC) formulation and then solved using the sequentially convex relaxation method. Compared with the classical gray-box identification methods like the prediction-error method (PEM), the new approach turns out to be more robust against converging to non-global minima, as supported by a simulation study. The developed identification can either be directly used for gray-box identification or provide an initial parameter estimate for the PEM. (C) 2018 Elsevier Ltd. All rights reserved.

  • 3752.
    Yu, Chengpu
    et al.
    Beijing Inst Technol, Peoples R China; Delft Univ Technol, Netherlands.
    Verhaegen, Michel
    Delft Univ Technol, Netherlands.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Subspace Identification of Local Systems in One-Dimensional Homogeneous Networks2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 4, p. 1126-1131Article in journal (Refereed)
    Abstract [en]

    This note considers the identification of large-scale one-dimensional networks consisting of identical LTI dynamical systems. A subspace identification method is developed that only uses local input-output information and does not rely on knowledge about the local state interaction. The proposed identification method estimates the Markov parameters of a locally lifted system, following the state-space realization of a single subsystem. The Markov-parameter estimation is formulated as a rank minimization problem by exploiting the low-rank property and the two-layer Toeplitz structural property in the data equation, whereas the state-space realization of a single subsystem is formulated as a structured low-rank matrix-factorization problem. The effectiveness of the proposed identification method is demonstrated by simulation examples.

  • 3753.
    Yuan, Zhen-Dong
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Insight into Neural Network Models for Nonlinear System identification1991Report (Other academic)
  • 3754.
    Yuan, Zhen-Dong
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Unprejudiced Optimal Open Loop Input Design for Identification of Transfer Functions1984Report (Other academic)
    Abstract [en]

    The problem to estimate transfer functions of linear systems is considered. The quality of the resulting estimate depends, among other things, on the input used during the identification experiment. We measure the quality using a quadratic norm in the frequency domain. The problem to determine optimal inputs, i.e. inputs that minimize the chosen norm, subject to constrained input variance, has long been studied. We point out that such procedures may involve a prejudice (that the system is to be found in a certain model set) that may have some surprising effects. We discuss how such a prejudice can be reduced by allowing the possibility that the true system cannot be exactly described in the chosen model set. We also calculate explicit expressions for the resulting “unprejudiced” optimal inputs. These expressions relate the signal-to-noise ratio (as a function of frequency) to the chosen weighting function in the quadratic norm. We also point out the role of the employed noise model for the design.

  • 3755.
    Yuan, Zhen-Dong
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Black-Box Identification of Multivariable Transfer Functions: Asymptotic Properties and Optimal Input Design1983Report (Other academic)
    Abstract [en]

    The problem of estimating the transfer function of a multivariable linear stochastic system is considered. The transfer function is parametrized as a black box and no order is chosen a priori. This means that the model order may increase to infinity as the number of observed data tends to infinity. The asymptotic covariance of the transfer function estimate is calculated and is found to be independent of the noise model when the model order increases to infinity. The derived expressions are also used to determine optimal ' unprejudiced ' input signals for the identification experiment.

  • 3756.
    Yuan, Zhen-Dong
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Optimal Input Design by Frequency Domain Criteria1982In: Proceedings of the 21st IEEE Conference on Decision and Control, 1982, p. 1005-1006Conference paper (Refereed)
    Abstract [en]

    Some explicit, analytical result on optimal input design for identification of transfer functions are derived. The results are asymptotic as the model order increases. This can be interpreted as a reduction of prejudice in the design; the prejudice being that the system is "known" to belong to a certain low-order model set.

  • 3757.
    Yuan, Zhen-Dong
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Unprejudiced Optimal Input Design for Identification of Transfer Functions1983Report (Other academic)
    Abstract [en]

    The problem to estimate transfer functions of linear systems is considered. The quality of the resulting estimate depends, among other things, on the input used during the identification experiment. We measure the quality using a quadratic norm in the frequency domain. The problem to determine optimal inputs, i.e. inputs that minimize the chosen norm, subject to constrained input variance, has long been studied. We point out that such procedures may involve a prejudice (that the system is to be found in a certain model set) that may have some surprising effects. We discuss how such a prejudice can be reduced by allowing the possibility that the true system cannot be exactly described in the chosen model set. We also calculate explicit expressions for the resulting “unprejudiced” optimal inputs. These expressions relate the signal-to-noise ratio (as a function of frequency) to the chosen weighting function in the quadratic norm. We also point out the role of the employed noise model for the design.

  • 3758.
    Yuan, Zhen-Dong
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Uprejudiced Optimal Open Loop Input Design for Identification of Transfer Functions1985In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 21, no 6, p. 697-708Article in journal (Refereed)
    Abstract [en]

    The problem to estimate transfer functions of linear systems is considered. The quality of the resulting estimate depends, among other things, on the input used during the identification experiment. We measure the quality using a quadratic norm in the frequency domain. The problem to determine optimal inputs, i.e. inputs that minimize the chosen norm, subject to constrained input variance, has long been studied. We point out that such procedures may involve a prejudice (that the system is to be found in a certain model set) that may have some surprising effects. We discuss how such a prejudice can be reduced by allowing the possibility that the true system cannot be exactly described in the chosen model set. We also calculate explicit expressions for the resulting “unprejudiced” optimal inputs. These expressions relate the signal-to-noise ratio (as a function of frequency) to the chosen weighting function in the quadratic norm. We also point out the role of the employed noise model for the design.

  • 3759.
    Yue, Zuogong
    et al.
    Univ Luxembourg, Luxembourg.
    Thunberg, Johan
    Univ Luxembourg, Luxembourg.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Goncalves, Jorge
    Univ Luxembourg, Luxembourg.
    On Definition and Inference of Nonlinear Boolean Dynamic Networks2017In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    Network reconstruction has become particularly important in systems biology, and is now expected to deliver information on causality. Systems in nature are inherently nonlinear. However, for nonlinear dynamical systems with hidden states, how to give a useful definition of dynamic networks is still an open question. This paper presents a useful definition of Boolean dynamic networks for a large class of nonlinear systems. Moreover, a robust inference method is provided. The well-known Millar-10 model in systems biology is used as a numerical example, which provides the ground truth of causal networks for key mRNAs involved in eukaryotic circadian clocks. In addition, as second contribution of this paper, we suggest definitions of linear network identifiability, which helps to unify the available work on network identifiability.

  • 3760.
    Yue, Zuogong
    et al.
    Univ Luxembourg, Luxembourg.
    Thunberg, Johan
    Univ Luxembourg, Luxembourg.
    Pan, Wei
    Imperial Coll London, England; Imperial Coll London, England.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Goncalves, Jorge
    Univ Luxembourg, Luxembourg.
    Linear Dynamic Network Reconstruction from Heterogeneous Datasets2017In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2017, Vol. 50, no 1, p. 10586-10591Conference paper (Refereed)
    Abstract [en]

    This paper addresses reconstruction of linear dynamic networks from heterogeneous datasets. Those datasets consist of measurements from linear dynamical systems in multiple experiments subjected to different experimental conditions, e.g., changes/perturbations in parameters, disturbance or noise. A main assumption is that the Boolean structures of the underlying networks are the same in all experiments. The ARMAX model is adopted to parameterize the general linear dynamic network representation "Dynamical Structure Function" (DSF), which provides the Granger Causality graph as a special case. The network identification is performed by integrating all available datasets and promote group sparsity to assure both network sparsity and the consistency of Boolean structures over datasets. In terms of solving the problem, a treatment by the iterative reweighted l(1) method is used, together with its implementations via proximal methods and ADMM for large-dimensional networks. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  • 3761.
    Zenere, Alberto
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Zorzi, Mattia
    Univ Padua, Italy.
    On the coupling of model predictive control and robust Kalman filtering2018In: IET Control Theory & Applications, ISSN 1751-8644, E-ISSN 1751-8652, Vol. 12, no 13, p. 1873-1881Article in journal (Refereed)
    Abstract [en]

    Model predictive control (MPC) represents nowadays one of the main methods employed for process control in industry. Its strong suits comprise a simple algorithm based on a straightforward formulation and the flexibility to deal with constraints. On the other hand, it can be questioned its robustness regarding model uncertainties and external noises. Thus, a lot of efforts have been spent in the past years into the search of methods to address these shortcomings. In this study, the authors propose a robust MPC controller which stems from the idea of adding robustness in the prediction phase of the algorithm while leaving the core of MPC untouched. More precisely, they consider a robust Kalman filter that has been recently introduced and they further extend its usability to feedback control systems. Overall the proposed control algorithm allows to maintain all of the advantages of MPC with an additional improvement in performance and without any drawbacks in terms of computational complexity. To test the actual reliability of the algorithm, they apply it to control a servomechanism system characterised by non-linear dynamics.

  • 3762.
    Zhang, Liang
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Network Capacity, Coverage Estimation and Frequency Planning of 3GPP Long Term Evolution2010Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The recent increase of mobile data usage and emergence of new applications such as Online Gaming, mobile TV, Web 2.0, Streaming Contents have greatly motivated the 3rd Generation Partnership Project (3GPP) to work on the Long Term Evolution (LTE). The LTE is the latest standard in the mobile network technology tree. It inherits and develops the GSM/EDGE and UMTS/HSPA network technologies and is a step toward the 4th generation (4G) of radio technologies designed to optimize the capacity and speed of 3G mobile communication networks. In this thesis, the LTE system capacity and coverage are investigated and a model is proposed on the base of the Release 8 of 3GPP LTE standards. After that, the frequency planning of LTE is also studied. The results cover the interference limited coverage calculation, the traffic capacity calculation and radio frequency assignment. The implementation is achieved on the WRAP software platform for the LTE Radio Planning.

    Download full text (pdf)
    FULLTEXT02
  • 3763.
    Zhang, Qinghua
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Wavelet Network: The Radial Structure and an Efficient Initialization Procedure1992Report (Other academic)
  • 3764.
    Zhang, Qinghua
    et al.
    IRISA, France.
    Iouditski, Anatoli
    INRIA, France.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identification of Wiener Systems with Monotonous Nonlinearity2007Report (Other academic)
    Abstract [en]

    A Wiener system is composed of a linear dynamic subsystem followed by a static nonlinearity. It is well known in the literature that the identification of the linear subsystem of a Wiener system can be separated from that of the output nonlinearity, if the input signal is Gaussian distributed. In order to deal with the non Gaussian input case, two new algorithms are proposed in this paper for direct identification of the linear subsystem, regardless of any parametrization of the output nonlinearity. The essential assumption required in this paper is the strict monotonousness of the output nonlinearity.

    Download full text (pdf)
    FULLTEXT01
  • 3765.
    Zhang, Qinghua
    et al.
    Inria IFSTTAR, France.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    From structurally independent local LTI models to LPV model*2017In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 84, p. 232-235Article in journal (Refereed)
    Abstract [en]

    The local approach to linear parameter varying (LPV) system identification consists in interpolating individually estimated local linear time invariant (LTI) models corresponding to fixed values of the scheduling variable. It is shown in this paper that, without any global structural assumption of the considered LPV system, individually estimated local state-space LTI models do not contain sufficient information for determining similarity transformations making them coherent. It is possible to estimate these similarity transformations from input-output data under appropriate excitation conditions. (C) 2017 Published by Elsevier Ltd.

    Download full text (pdf)
    fulltext
  • 3766.
    Zhang, Qinghua
    et al.
    IRISA-INRIA, France.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Multiple Steps Prediction with Nonlinear ARX Models2004In: Proceedings of the 2004 IFAC Symposium on Nonlinear Control Systems, 2004Conference paper (Refereed)
    Abstract [en]

    Abstract NLARX (NonLinear AutoRegressive with eXogenous inputs) models are frequently used in black-box nonlinear system identication. Though it is easy to make one step ahead prediction with such models, multiple steps prediction is far from trivial. The main difficulty is that in general there is no easy way to compute the mathematical expectation of an output conditioned by past measurements. An optimal solution would require intensive numerical computations related to nonlinear filltering. The purpose of this paper is to investigate simple non optimal prediction methods. It is shown that cautions must be paid when using such methods, since their prediction behaviors may be radically different, depending on some detailed choice.

  • 3767.
    Zhang, Qinghua
    et al.
    IRISA-INRIA, France.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Multiple Steps Prediction with Nonlinear ARX Models2007Report (Other academic)
    Abstract [en]

    NLARX (NonLinear AutoRegressive with eXogenous inputs) models are frequently used in black-box nonlinear system identication. Though it is easy to make one step ahead prediction with such models, multiple steps prediction is far from trivial. The main difficulty is that in general there is no easy way to compute the mathematical expectation of an output conditioned by past measurements. An optimal solution would require intensive numerical computations related to nonlinear filltering. The purpose of this paper is to investigate simple non optimal prediction methods. It is shown that cautions must be paid when using such methods, since their prediction behaviors may be radically different, depending on some detailed choice.

    Download full text (pdf)
    FULLTEXT01
  • 3768.
    Zhang, Qinghua
    et al.
    Institut de Recherche en Informatique et Systèmes Aléatoires, France.
    Wang, Jiandong
    Peking University, China.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Optimality Analysis of the Two-Stage Algorithm for Hammerstein System Identification2009Report (Other academic)
    Abstract [en]

    The Two-Stage Algorithm (TSA) has been extensively used and adapted for the identification of Hammerstein systems. It is essentially based on a particular formulation of Hammerstein systems in the form of bilinearly parameterized linear regressions. This paper has been motivated by a somewhat contradictory fact: though the optimality of the TSA has been established by Bai in 1998 only in the case of some special weighting matrices, the unweighted TSA is usually used in practice. It is shown in this paper that the unweighted TSA indeed gives the optimal solution of the weighted nonlinear least-squares problem formulated with a particular weighting matrix. This provides a theoretical justification of the unweighted TSA, and leads to a generalization of the obtained result to the case of colored noise with noise whitening. Numerical examples of identification of Hammerstein systems are presented to validate the theoretical analysis.

    Download full text (pdf)
    FULLTEXT01
  • 3769.
    Zhao, Yuxin
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gaussian Processes for Positioning Using Radio Signal Strength Measurements2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Estimation of unknown parameters is considered as one of the major research areas in statistical signal processing. In the most recent decades, approaches in estimation theory have become more and more attractive in practical applications. Examples of such applications may include, but are not limited to, positioning using various measurable radio signals in indoor environments, self-navigation for autonomous cars, image processing, radar tracking and so on. One issue that is usually encountered when solving an estimation problem is to identify a good system model, which may have great impacts on the estimation performance. In this thesis, we are interested in studying estimation problems particularly in inferring the unknown positions from noisy radio signal measurements. In addition, the modeling of the system is studied by investigating the relationship between positions and radio signal strength measurements.

    One of the main contributions of this thesis is to propose a novel indoor positioning framework based on proximity measurements, which are obtained by quantizing the received signal strength measurements. Sequential Monte Carlo methods, to be more specific particle filter and smoother, are utilized for estimating unknown positions from proximity measurements. The Cramér-Rao bounds for proximity-based positioning are further derived as a benchmark for the positioning accuracy in this framework.

    Secondly, to improve the estimation performance, Bayesian non-parametric modeling, namely Gaussian processes, have been adopted to provide more accurate and flexible models for both dynamic motions and radio signal strength measurements. Then, the Cramér-Rao bounds for Gaussian process based system models are derived and evaluated in an indoor positioning scenario.

    In addition, we estimate the positions of stationary devices by comparing the individual signal strength measurements with a pre-constructed fingerprinting database. The positioning accuracy is further compared to the case where a moving device is positioned using a time series of radio signal strength measurements.

    Moreover, Gaussian processes have been applied to sports analytics, where trajectory modeling for athletes is studied. The proposed framework can be further utilized to carry out, for instance, performance prediction and analysis, health condition monitoring, etc. Finally, a grey-box modeling is proposed to analyze the forces, particularly in cross-country skiing races, by combining a deterministic kinetic model with Gaussian process.

    List of papers
    1. Received-Signal-Strength Threshold Optimization Using Gaussian Processes
    Open this publication in new window or tab >>Received-Signal-Strength Threshold Optimization Using Gaussian Processes
    2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 8, p. 2164-2177Article in journal (Refereed) Published
    Abstract [en]

    There is a big trend nowadays to use event-triggered proximity report for indoor positioning. This paper presents a generic received-signal-strength (RSS) threshold optimization framework for generating informative proximity reports. The proposed framework contains five main building blocks, namely the deployment information, RSS model, positioning metric selection, optimization process and management. Among others, we focus on Gaussian process regression (GPR)-based RSS models and positioning metric computation. The optimal RSS threshold is found through minimizing the best achievable localization root-mean-square-error formulated with the aid of fundamental lower bound analysis. Computational complexity is compared for different RSS models and different fundamental lower bounds. The resulting optimal RSS threshold enables enhanced performance of new fashioned low-cost and low-complex proximity report-based positioning algorithms. The proposed framework is validated with real measurements collected in an office area where bluetooth-low-energy (BLE) beacons are deployed.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2017
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-135065 (URN)10.1109/TSP.2017.2655480 (DOI)000395827100018 ()
    Projects
    TRAX
    Note

    Funding agencies: European Union FP7 Marie Curie training programme on Tracking in Complex Sensor Systems [607400]

    Available from: 2017-03-08 Created: 2017-03-08 Last updated: 2019-02-12Bibliographically approved
    2. Sequential Monte Carlo Methods and Theoretical Bounds for Proximity Report Based Indoor Positioning
    Open this publication in new window or tab >>Sequential Monte Carlo Methods and Theoretical Bounds for Proximity Report Based Indoor Positioning
    Show others...
    2018 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 6, p. 5372-5386Article in journal (Refereed) Published
    Abstract [en]

    The commercial interest in proximity services is increasing. Application examples include location-based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider positioning of devices based on a time series of proximity reports from a mobile device to a network node. This corresponds to nonlinear measurements with respect to the device position in relation to the network nodes. Motion model will be needed together with the measurements to determine the position of the device. Therefore, sequential Monte Carlo methods, namely particle filtering and smoothing, are applicable for positioning. Positioning performance is evaluated in a typical office area with Bluetooth-low-energy beacons deployed for proximity detection and report, and is further compared to parametric Cramér-Rao lower bounds. Finally, the position accuracy is also evaluated with real experimental data.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2018
    Keywords
    Proximity, indoor positioning, particle filtering and smoothing, Cramer-Rao lower bounds
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-147834 (URN)10.1109/TVT.2018.2799174 (DOI)000435553400053 ()2-s2.0-85041415767 (Scopus ID)
    Note

    Funding agencies: European Union FP7 Marie Curie Training Programme on Tracking in Complex Sensor Systems (TRAX) [607400]; NSFC [61701426]; Shenzhen Science and Technology Innovation Council [JCYJ20170307155957688, JCYJ20170411102101881]

    Available from: 2018-05-15 Created: 2018-05-15 Last updated: 2019-02-12Bibliographically approved
    3. Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning
    Open this publication in new window or tab >>Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning
    Show others...
    2016 (English)In: 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), IEEE , 2016, p. 1-5Conference paper, Published paper (Refereed)
    Abstract [en]

    The commercial interest in proximity services is increasing. Application examples include location-based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider network-based positioning based on times series of proximity reports from a mobile device, either only a proximity indicator, or a vector of RSS from observed nodes. Such positioning corresponds to a latent and nonlinear observation model. To address these problems, we combine two powerful tools, namely particle filtering and Gaussian process regression (GPR) for radio signal propagation modeling. The latter also provides some insights into the spatial correlation of the radio propagation in the considered area. Radio propagation modeling and positioning performance are evaluated in a typical office area with Bluetooth-Low-Energy (BLE) beacons deployed for proximity detection and reports. Results show that the positioning accuracy can be improved by using GPR.

    Place, publisher, year, edition, pages
    IEEE, 2016
    National Category
    Communication Systems
    Identifiers
    urn:nbn:se:liu:diva-128255 (URN)10.1109/VTCSpring.2016.7504255 (DOI)000386528400206 ()9781509016983 (ISBN)
    Conference
    2016 IEEE 83rd Vehicular Technology Conference: VTC2016-Spring, 15–18 May 2016, Nanjing, China
    Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2019-02-12Bibliographically approved
    4. Gaussian processes for RSS fingerprints construction in indoor localization
    Open this publication in new window or tab >>Gaussian processes for RSS fingerprints construction in indoor localization
    2018 (English)In: 21st International Conference on Information Fusion (FUSION), IEEE, 2018, p. 1377-1384Conference paper, Published paper (Refereed)
    Abstract [en]

    Location-based applications attract more and more attention in recent years. Examples of such applications include commercial advertisements, social networking software and patient monitoring. The received signal strength (RSS) based location fingerprinting is one of the most popular solutions for indoor localization. However, there is a big challenge in collecting and maintaining a relatively large RSS fingerprint database. In this work, we propose and compare two algorithms namely, the Gaussian process (GP) and Gaussian process with variogram, to estimate and construct the RSS fingerprints with incomplete data. The fingerprint of unknown reference points is estimated based on measurements at a limited number of surrounding locations. To validate the effectiveness of both algorithms, experiments using Bluetooth-low-energy (BLE) infrastructure have been conducted. The constructed RSS fingerprints are compared to the true measurements, and the result is analyzed. Finally, using the constructed fingerprints, the localization performance of a probabilistic fingerprinting method is evaluated.

    Place, publisher, year, edition, pages
    IEEE, 2018
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-151693 (URN)10.23919/ICIF.2018.8455842 (DOI)978-0-9964527-6-2 (ISBN)
    Conference
    21st International Conference on Information Fusion (FUSION), 10-13 July 2018, Cambridge, UK
    Available from: 2018-10-01 Created: 2018-10-01 Last updated: 2019-02-12
    5. Gaussian Processes for Flow Modeling and Prediction of Positioned Trajectories Evaluated with Sports Data
    Open this publication in new window or tab >>Gaussian Processes for Flow Modeling and Prediction of Positioned Trajectories Evaluated with Sports Data
    Show others...
    2016 (English)In: 19th International Conference on  Information Fusion (FUSION), 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1461-1468Conference paper, Published paper (Refereed)
    Abstract [en]

    Kernel-based machine learning methods are gaining increasing interest in flow modeling and prediction in recent years. Gaussian process (GP) is one example of such kernelbased methods, which can provide very good performance for nonlinear problems. In this work, we apply GP regression to flow modeling and prediction of athletes in ski races, but the proposed framework can be generally applied to other use cases with device trajectories of positioned data. Some specific aspects can be addressed when the data is periodic, like in sports where the event is split up over multiple laps along a specific track. Flow models of both the individual skier and a cluster of skiers are derived and analyzed. Performance has been evaluated using data from the Falun Nordic World Ski Championships 2015, in particular the Men’s cross country 4 × 10 km relay. The results show that the flow models vary spatially for different skiers and clusters. We further demonstrate that GP regression provides powerful and accurate models for flow prediction.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering Probability Theory and Statistics
    Identifiers
    urn:nbn:se:liu:diva-129758 (URN)9780996452748 (ISBN)9781509020126 (ISBN)
    Conference
    19th International Conference on Information Fusion, 5-8 July 2016, Heidelberg, Germany
    Available from: 2016-06-27 Created: 2016-06-27 Last updated: 2019-02-12Bibliographically approved
    Download full text (pdf)
    Gaussian Processes for Positioning Using Radio Signal Strength Measurements
    Download (png)
    presentationsbild
  • 3770. Order onlineBuy this publication >>
    Zhao, Yuxin
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Position Estimation in Uncertain Radio Environments and Trajectory Learning2017Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    To infer the hidden states from the noisy observations and make predictions based on a set of input states and output observations are two challenging problems in many research areas. Examples of applications many include position estimation from various measurable radio signals in indoor environments, self-navigation for autonomous cars, modeling and predicting of the traffic flows, and flow pattern analysis for crowds of people. In this thesis, we mainly use the Bayesian inference framework for position estimation in an indoor environment, where the radio propagation is uncertain. In Bayesian inference framework, it is usually hard to get analytical solutions. In such cases, we resort to Monte Carlo methods to solve the problem numerically. In addition, we apply Bayesian nonparametric modeling for trajectory learning in sport analytics.

    The main contribution of this thesis is to propose sequential Monte Carlo methods, namely particle filtering and smoothing, for a novel indoor positioning framework based on proximity reports. The experiment results have been further compared with theoretical bounds derived for this proximity based positioning system. To improve the performance, Bayesian non-parametric modeling, namely Gaussian process, has been applied to better indicate the radio propagation conditions. Then, the position estimates obtained sequentially using filtering and smoothing are further compared with a static solution, which is known as fingerprinting.

    Moreover, we propose a trajectory learning framework for flow estimation in sport analytics based on Gaussian processes. To mitigate the computation deficiency of Gaussian process, a grid-based on-line algorithm has been adopted for real-time applications. The resulting trajectory modeling for individual athlete can be used for many purposes, such as performance prediction and analysis, health condition monitoring, etc. Furthermore, we aim at modeling the flow of groups of athletes, which could be potentially used for flow pattern recognition, strategy planning, etc.

    List of papers
    1. Received-Signal-Strength Threshold Optimization Using Gaussian Processes
    Open this publication in new window or tab >>Received-Signal-Strength Threshold Optimization Using Gaussian Processes
    2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 8, p. 2164-2177Article in journal (Refereed) Published
    Abstract [en]

    There is a big trend nowadays to use event-triggered proximity report for indoor positioning. This paper presents a generic received-signal-strength (RSS) threshold optimization framework for generating informative proximity reports. The proposed framework contains five main building blocks, namely the deployment information, RSS model, positioning metric selection, optimization process and management. Among others, we focus on Gaussian process regression (GPR)-based RSS models and positioning metric computation. The optimal RSS threshold is found through minimizing the best achievable localization root-mean-square-error formulated with the aid of fundamental lower bound analysis. Computational complexity is compared for different RSS models and different fundamental lower bounds. The resulting optimal RSS threshold enables enhanced performance of new fashioned low-cost and low-complex proximity report-based positioning algorithms. The proposed framework is validated with real measurements collected in an office area where bluetooth-low-energy (BLE) beacons are deployed.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2017
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-135065 (URN)10.1109/TSP.2017.2655480 (DOI)000395827100018 ()
    Projects
    TRAX
    Note

    Funding agencies: European Union FP7 Marie Curie training programme on Tracking in Complex Sensor Systems [607400]

    Available from: 2017-03-08 Created: 2017-03-08 Last updated: 2019-02-12Bibliographically approved
    2. Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning
    Open this publication in new window or tab >>Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning
    Show others...
    2016 (English)In: 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), IEEE , 2016, p. 1-5Conference paper, Published paper (Refereed)
    Abstract [en]

    The commercial interest in proximity services is increasing. Application examples include location-based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider network-based positioning based on times series of proximity reports from a mobile device, either only a proximity indicator, or a vector of RSS from observed nodes. Such positioning corresponds to a latent and nonlinear observation model. To address these problems, we combine two powerful tools, namely particle filtering and Gaussian process regression (GPR) for radio signal propagation modeling. The latter also provides some insights into the spatial correlation of the radio propagation in the considered area. Radio propagation modeling and positioning performance are evaluated in a typical office area with Bluetooth-Low-Energy (BLE) beacons deployed for proximity detection and reports. Results show that the positioning accuracy can be improved by using GPR.

    Place, publisher, year, edition, pages
    IEEE, 2016
    National Category
    Communication Systems
    Identifiers
    urn:nbn:se:liu:diva-128255 (URN)10.1109/VTCSpring.2016.7504255 (DOI)000386528400206 ()9781509016983 (ISBN)
    Conference
    2016 IEEE 83rd Vehicular Technology Conference: VTC2016-Spring, 15–18 May 2016, Nanjing, China
    Available from: 2016-05-24 Created: 2016-05-24 Last updated: 2019-02-12Bibliographically approved
    3. Gaussian Processes for Flow Modeling and Prediction of Positioned Trajectories Evaluated with Sports Data
    Open this publication in new window or tab >>Gaussian Processes for Flow Modeling and Prediction of Positioned Trajectories Evaluated with Sports Data
    Show others...
    2016 (English)In: 19th International Conference on  Information Fusion (FUSION), 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1461-1468Conference paper, Published paper (Refereed)
    Abstract [en]

    Kernel-based machine learning methods are gaining increasing interest in flow modeling and prediction in recent years. Gaussian process (GP) is one example of such kernelbased methods, which can provide very good performance for nonlinear problems. In this work, we apply GP regression to flow modeling and prediction of athletes in ski races, but the proposed framework can be generally applied to other use cases with device trajectories of positioned data. Some specific aspects can be addressed when the data is periodic, like in sports where the event is split up over multiple laps along a specific track. Flow models of both the individual skier and a cluster of skiers are derived and analyzed. Performance has been evaluated using data from the Falun Nordic World Ski Championships 2015, in particular the Men’s cross country 4 × 10 km relay. The results show that the flow models vary spatially for different skiers and clusters. We further demonstrate that GP regression provides powerful and accurate models for flow prediction.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering Probability Theory and Statistics
    Identifiers
    urn:nbn:se:liu:diva-129758 (URN)9780996452748 (ISBN)9781509020126 (ISBN)
    Conference
    19th International Conference on Information Fusion, 5-8 July 2016, Heidelberg, Germany
    Available from: 2016-06-27 Created: 2016-06-27 Last updated: 2019-02-12Bibliographically approved
    Download full text (pdf)
    Position Estimation in Uncertain Radio Environments and Trajectory Learning
    Download (pdf)
    omslag
    Download (jpg)
    presentationsbild
  • 3771.
    Zhao, Yuxin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Fritsche, Carsten
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Supplementary Materials for "Sequential Monte Carlo Methods and Theoretical Bounds for Proximity Report based Indoor Positioning"2017Report (Other academic)
    Abstract [en]

    This reportontains supplementary material for the paper [1].

    Download full text (pdf)
    fulltext
  • 3772.
    Zhao, Yuxin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Fritsche, Carsten
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gunnarsson, Fredrik
    Ericsson AB.
    Parametric Lower Bound for Nonlinear Filteringbased on Gaussian Process Regression Model2017In: 2017 20th International Conference on Information Fusion (Fusion), IEEE, 2017, p. 1-7Conference paper (Refereed)
    Abstract [en]

    Assessing the fundamental performance limitationsin Bayesian filtering can be carried out using the parametricCram´er-Rao bound (CRB). The parametric CRB puts a lowerbound on mean square error (MSE) matrix conditioned on aspecific state trajectory realization. In this work, we derive theparametric CRB for state-space models, where the measurementequation is modeled by a Gaussian process regression.These models appear, for instance in proximity report-basedpositioning, where proximity reports are obtained by hardthresholding of received signal strength (RSS) measurements, thatare modeled through Gaussian process regression. The proposedparametric CRB is evaluated on selected state trajectories andfurther compared with the positioning performance obtained bythe particle filter. The results corroborate that the positioningaccuracy achieved in this framework is close to the parametricCRB.

    Download full text (pdf)
    fulltext
  • 3773.
    Zhao, Yuxin
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering. Ericsson.
    Fritsche, Carsten
    Linköping University, Faculty of Science & Engineering. Linköping University, Department of Electrical Engineering, Automatic Control.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Linköping University, Faculty of Science & Engineering. Linköping University.
    Yin, Feng
    Chinese University of Hong Kong (Shenzhen).
    Chen, Tianshi
    Chinese University of Hong Kong (Shenzhen).
    Gunnarsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Cramér–Rao Bounds for Filtering Based on Gaussian Process State-Space Models2019In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, no 23, p. 5936-5951Article in journal (Refereed)
    Abstract [en]

    Posterior Cramér-Rao bounds (CRBs) are derived for the estimation performance of three Gaussian process-based state-space models. The parametric CRB is derived for the case with a parametric state transition and a Gaussian process-based measurement model. We illustrate the theory with a target tracking example and derive both parametric and posterior filtering CRBs for this specific application. Finally, the theory is illustrated with a positioning problem, with experimental data from an office environment where the obtained estimation performance is compared to the derived CRBs.

    Download full text (pdf)
    Cramér–Rao Bounds for Filtering Based on Gaussian Process State-Space Models
    Download full text (pdf)
    Supplementary Material for Cramér–Rao Bounds  for Filtering Based on Gaussian Process State‐ Space Models
  • 3774.
    Zhao, Yuxin
    et al.
    Research, Ericsson AB, 39174 Stockholm, Sweden.
    Fritsche, Carsten
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Yin, Feng
    SSE, Chinese University of Hong Kong Shenzhen, Shenzhen, China.
    Gunnarsson, Fredrik
    Ericsson Research, Linköping, Sweden.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Sequential Monte Carlo Methods and Theoretical Bounds for Proximity Report Based Indoor Positioning2018In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 6, p. 5372-5386Article in journal (Refereed)
    Abstract [en]

    The commercial interest in proximity services is increasing. Application examples include location-based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider positioning of devices based on a time series of proximity reports from a mobile device to a network node. This corresponds to nonlinear measurements with respect to the device position in relation to the network nodes. Motion model will be needed together with the measurements to determine the position of the device. Therefore, sequential Monte Carlo methods, namely particle filtering and smoothing, are applicable for positioning. Positioning performance is evaluated in a typical office area with Bluetooth-low-energy beacons deployed for proximity detection and report, and is further compared to parametric Cramér-Rao lower bounds. Finally, the position accuracy is also evaluated with real experimental data.

    Download full text (pdf)
    fulltext
  • 3775.
    Zhao, Yuxin
    et al.
    Ericsson Research, Linköping, Sweden.
    Yin, Feng
    Ericsson Research, Linköping, Sweden.
    Gunnarsson, Fredrik
    Ericsson Research, Linköping, Sweden.
    Amirijoo, Mehdi
    Ericsson Research, Linköping, Sweden.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gaussian Process for Propagation modeling and Proximity Reports Based Indoor Positioning2016In: 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), IEEE , 2016, p. 1-5Conference paper (Refereed)
    Abstract [en]

    The commercial interest in proximity services is increasing. Application examples include location-based information and advertisements, logistics, social networking, file sharing, etc. In this paper, we consider network-based positioning based on times series of proximity reports from a mobile device, either only a proximity indicator, or a vector of RSS from observed nodes. Such positioning corresponds to a latent and nonlinear observation model. To address these problems, we combine two powerful tools, namely particle filtering and Gaussian process regression (GPR) for radio signal propagation modeling. The latter also provides some insights into the spatial correlation of the radio propagation in the considered area. Radio propagation modeling and positioning performance are evaluated in a typical office area with Bluetooth-Low-Energy (BLE) beacons deployed for proximity detection and reports. Results show that the positioning accuracy can be improved by using GPR.

    Download full text (pdf)
    fulltext
  • 3776.
    Zhen-Dong, Yuan
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Optimal Input Design by Frequency Domain Criteria1982Report (Other academic)
    Abstract [en]

    Some explicit, analytical result on optimal input design for identification of transfer functions are derived. The results are asymptotic as the model order increases. This can be interpreted as a reduction of prejudice in the design; the prejudice being that the system is "known" to belong to a certain low-order model set.

  • 3777.
    Zrida, Jalel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Matlab Implementation of Stochastic and Classification Tree Manipulations1989Report (Other academic)
  • 3778.
    Zrida, Jalel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Strömberg, Jan-Erik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Applying Tree Classifier Methods to a Speech Recognition Problem: A Study of the Neural Tree Concept1990Report (Other academic)
  • 3779.
    Åberg Skender, Dennis
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Modelling of Test Bench for Road Load Simulation2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Warehouse forklifts are often powered by batteries. By using a test bench where the forklift can be driven in a certain driving-cycle, the battery capacity can be tested. To obtain the same speed curve on the test bench as a forklift obtains when driving on a real road, the test bench must be able to simulate road load. In this master’s thesis, a test bench is modelled in Simulink using grey-box modelling and validated with measured data. Also, a speed regulator is developed and implemented in the test bench model to simulate road load. Simulations with the model and the speed regulator show high accuracy when compared against measured data. However, the results show that the pre-attached torque sensor is not optimally located, and that the gear oil temperature is of interest to measure to be able to model the friction torque as a function of the temperature.

    Download full text (pdf)
    fulltext
  • 3780.
    Åkerblad, Magnus
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    A Second Order Cone Programming Algorithm for Model Predictive Control2004Report (Other academic)
    Abstract [en]

    In Model Predictive Control (MPC) an optimal control problem has to be solved at each sampling instant. The objective of this thesis is to derive efficient methods to solve the MPC optimization problem. The approach is based on ideas from Interior Point (IP) optimization methods and Riccati recursions. The MPC problem considered here has a quadratic objective and constraints which can be both linear and quadratic. The key to an efficient implementation is to rewrite the optimization problem as a Second Order Cone Program (SOCP). To solve the SOCP a feasible primal-dual IP method is employed. By using a feasible IP method it is possible to determine when the problem is feasible or not by formalizing the search for strictly feasible initial points as a primal-dual IP problem. There are several different ways to rewrite the optimization problem as an SOCP. However, done carefully, it is possible to use very efficient scalings as well as Riccati recursions for computing the search directions. The use of Riccati recursions makes the computational complexity growat most quadratically with the time horizon, compared to cubically for more standard implementations.

    Download full text (pdf)
    FULLTEXT01
  • 3781.
    Åkerblad, Magnus
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Efficient Solution of Second Order Cone Program for Model Predictive Control2002Report (Other academic)
    Abstract [en]

    In this paper it is shown how to efficiently solve an optimal control problem with applications to model predictive control. The objective is quadratic and the constraints can be both linear and quadratic. The key to an efficient implementation is to rewrite the optimization problem as a second order cone program. This can be done in many different ways. However, done carefully, it is possible to use both very efficient scalings as well as Riccati recursions for computing the search directions.

    Download full text (pdf)
    FULLTEXT01
  • 3782.
    Åkerblad, Magnus
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hansson, Anders
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Efficient Solution of Second Order Cone Program for Model Predictive Control2004In: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 77, no 1, p. 55-77Article in journal (Refereed)
    Abstract [en]

    In model predictive control an optimization problem has to be solved at each sampling instant. The objective in this article is to derive efficient methods to solve this optimization problem. The approach taken is to use interior point optimization methods. The model predictive control problem considered here has a quadratic objective and constraints which can be both linear and quadratic. The key to an efficient implementation is to rewrite the optimization problem as a second order cone program. To solve this optimization problem a feasible primal-dual interior point method is employed. By using a feasible method it is possible to determine when the problem is feasible or not by formalizing the search for strictly feasible initial points as yet another primal-dual interior point problem. There are several different ways to rewrite the optimization problem as a second order cone program. However, done carefully, it is possible to use very efficient scalings as well as Riccati recursions for computing the search directions. The use of Riccati recursions makes the computational complexity grow at most as script, O sign(N 3/2) with the time horizon, compared to script O sign(N3) for more standard implementations.

  • 3783.
    Åstrand, Max
    et al.
    KTH Royal Institute of Technology, Stockholm; ABB Corporate Research, Västerås.
    Jakobsson, Erik
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering. Epiroc, Örebro.
    Lindfors, Martin
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Svensson, John
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering. Boliden Mines, Boliden, Sweden.
    A system for underground road condition monitoring2020In: International Journal of Mining Science and Technology, ISSN 2095-2686Article in journal (Refereed)
    Abstract [en]

    Poor road conditions in underground mine tunnels can lead to decreased production efficiency and increased wear on production vehicles. A prototype system for road condition monitoring is presented in this paper to counteract this. The system consists of three components i.e. localization, road monitoring, and scheduling. The localization of vehicles is performed using a Rao-Blackwellized extended particle filter, combining vehicle mounted sensors with signal strengths of WiFi access points. Two methods for road monitoring are described: a Kalman filter used together with a model of the vehicle suspension system, and a relative condition measure based on the power spectral density. Lastly, a method for taking automatic action on an ill-conditioned road segment is proposed in the form of a rescheduling algorithm. The scheduling algorithm is based on the large neighborhood search and is used to integrate road service activities in the short-term production schedule while minimizing introduced production disturbances. The system is demonstrated on experimental data collected in a Swedish underground mine.

    Download full text (pdf)
    fulltext
  • 3784.
    Åström, Karl J.
    et al.
    Lund University, Sweden.
    Benveniste, Albert
    INRIA, France.
    Caines, Peter E.
    INRIA, France.
    Cohen, Guy
    INRIA, France.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Facing the Challenge of Computer Science in the Industrial Applications of Control1992Report (Other academic)
    Abstract [en]

    Control, signal processing, and more generally "systems" industries ignore the boundaries we have in the academic world between control, signal processing, and computer sciences. Industries think of "hardware" (electronics or computers) and "software", making little distinction between algorithms development and implementation of them. Acting as a chariman of the IFAC Technical Committee on Theory for the triennium 1990-1993, Albert Benveniste proposed in the fall of 1989 this project to investigate some fundamental questions raised by the above mentioned facts. Since CDC'90 this has been approved as a joint IEEE/CSS-IFAC project managed by the above listed group of people. A detailed progress report of the project has been written in March 20, 1991, followed by a brief update in October 19, 1991. This is summary of the conclusions of the report. Additional detailed information on the project is found in the bibliography.

  • 3785.
    Åström, Karl Johan
    et al.
    Lund Institute of Technology, Sweden.
    Borisson, U
    Gränges Data, Sweden.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Wittenmark, Björn
    Lund Institute of Technology.
    Theory and Applications of Self Tuning Regulators1977In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 13, no 5, p. 457-476Article in journal (Refereed)
    Abstract [en]

    This paper reviews work on self-tuning regulators. The regulator algorithms, their theory and industrial applications are reviewed. The paper is expository—the major ideas are covered but detailed analysis is given elsewhere.

  • 3786.
    Öhr, Jonas
    et al.
    ABB, Sweden.
    Moberg, Stig
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Wernholt, Erik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hanssen, Sven
    ABB, Sweden.
    Pettersson, Jens
    ABB, Sweden.
    Persson, Sofie
    ABB, Sweden.
    Sander-Tavallaey, Shiva
    ABB, Sweden.
    Identification of Flexibility Parameters of 6-axis Industrial Manipulator Models2006In: Proceedings of the 2006 International Conference on Noise and Vibration Engineering, 2006, p. 3305-Conference paper (Refereed)
    Abstract [en]

    A method for identification of flexibility parameters of a 18 DOF (degrees offreedom) robot prototype model is proposed. Experiments show the strengthof the method and the results indicates that flexibilities in the bearings and thearms, taken together, are of the same order as the flexibilities in the gears.

  • 3787.
    Öhr, Jonas
    et al.
    ABB, Sweden.
    Moberg, Stig
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Wernholt, Erik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hanssen, Sven
    ABB, Sweden.
    Pettersson, Jens
    ABB, Sweden.
    Persson, Sofie
    ABB, Sweden.
    Sander-Tavallaey, Shiva
    ABB, Sweden.
    Identification of Flexibility Parameters of 6-axis Industrial Manipulator Models2006Report (Other academic)
    Abstract [en]

    A method for identification of flexibility parameters of a 18 DOF (degrees offreedom) robot prototype model is proposed. Experiments show the strengthof the method and the results indicates that flexibilities in the bearings and thearms, taken together, are of the same order as the flexibilities in the gears.

    Download full text (pdf)
    FULLTEXT01
  • 3788.
    Öhrn, Philip
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Åstrand, Markus
    Linköping University, Department of Electrical Engineering, Automatic Control.
    Direct Lift Control of Fighter Aircraft2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Direct lift control for aircraft has been around in the aeronautical industry for decades but is mainly used in commercial aircraft with dedicated direct lift control surfaces. The focus of this thesis is to investigate if direct lift control is feasible for a fighter aircraft, similar to Saab JAS 39 Gripen, without dedicated control surfaces.

    The modelled system is an aircraft that is inherently unstable and contains nonlinearities both in its aerodynamics and in the form of limited control surface deflection and deflection rates. The dynamics of the aircraft are linearised around a flight case representative of a landing scenario. Direct lift control is then applied to give a more immediate relation from pilot stick input to change in flight path angle while also preserving the pitch attitude.

    Two different control strategies, linear quadratic control and model predictive control, were chosen for the implementation. Since fighter aircraft are systems with fast dynamics it was important to limit the computational time. This constraint motivated the use of specialised methods to speed up the optimisation of the model predictive controller.

    Results from simulations in a nonlinear simulation environment supplied by Saab, as well as tests in high-fidelity flight simulation rigs with a pilot, proved that direct lift control is feasible for the investigated fighter aircraft. Sufficient control authority and performance when controlling the flight path angle were observed. Both developed controllers have their own advantages and which strategy is the most suitable depends on what the user prioritises. Pilot workload during landing as well as precision at touch down were deemed similar to conventional control.

    Download full text (pdf)
    fulltext
  • 3789.
    Öijerholm, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Department of Electrical Engineering.
    Aspects of the choice of sampling frequency in the control system of a gas turbine2009Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    At Siemens, plcs are used to control the gas turbines, and to execute the code in the plcs cyclic interrupts are used. If the execution time for the interrupt becomes close to the cyclic time of the interrupt the load of the plc increases. High load levels can lead to situations were segments of code are not executed on time or even not executed at all. In this thesis an analysis of the regulators used to govern a gas turbine has been performed. The purpose of the analysis is to study the performance of the regulators for different cycle times with the aim to be able to reduce the load by sampling more slowly.

    To determine the load contribution from each regulator a review of the regulators and their execution times has been made. For the analysis the Matlab program Simulink has been used to make models of the regulators, which have then been sampled at different rates. With this information it is possible to determine for which cycle times each regulator has accepetable performance and how much load each regulator contributes with. A save of load of approximately 2 percent can be obtained without loosing too much performance.

    Download full text (pdf)
    FULLTEXT01
  • 3790.
    Örn, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Szilassy, Martin
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Dil, Bram
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    A Novel Multi-Step Algorithm for Low-Energy Positioning Using GPS2016In: Fusion 2016, 19th International Conference on Information Fusion: Proceedings, 2016, p. 1469-1476Conference paper (Refereed)
    Abstract [en]

    GPS is widely used for localization and tracking, however traditional GPS receivers consume too much energy for many applications. This paper implements and evaluates the performance of a low-energy GPS prototype. The main difference is that a traditional GPS needs to sample signals transmitted by satellites for 30 seconds to estimate its position. Our prototype reduces this time by three orders of magnitude and it can compute positions from only 2 milliseconds of data. We present a new algorithm that increases robustness by filtering on estimated residuals instead of using an altitude database. In addition, we show that our new algorithm works with both fixed and moving targets. The solution consists of (1) a portable device that samples the GPS signal and (2) a server that utilizes Doppler navigation and Coarse Time Navigation to estimate positions. We performed tests in a wide variety of environments and situations. These tests show that our prototype provides a median positioning error of roughly 40 meters even when the GPS receiver is moving at 80 kilometres per hour.

    Download full text (pdf)
    fulltext
  • 3791.
    Öst, Gustav
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Search path generation with UAV applications using approximate convex decomposition2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This work focuses on the problem that pertains to area searching with UAVs. Specifically developing algorithms that generate flight paths that are short with- out sacrificing flyability. For instance, very sharp turns will compromise flyability since fixed wing aircraft cannot make very sharp turns. This thesis provides an analysis of different types of search methods, area decompositions, and combi- nations thereof. The search methods used are side to side searching and spiral searching. In side to side searching the aircraft goes back and forth only making 90-degree turns. Spiral search searches the shape in a spiral pattern starting on the outer perimeter working its way in. The idea being that it should generate flight paths that are easy to fly since all turns should be with a large turn radii. Area decomposition is done to divide complex shapes into smaller more manage- able shapes. The report concludes that with the implemented methods the side to side scanning method without area decomposition yields good and above all very reliable results. The reliability stems from the fact that all turns are 90 degrees and that algorithm never get stuck or makes bad mistakes. Only having 90 degree turns results in only four different types of turns. This allows the airplanes behav- ior along the route to be predictable after flying the first four turns. Although this assumes that the strength of the wind is a greater influence than the turbulences effect on the aircraft’s flight characteristics. This is a very valuable feature for an operator in charge of a flight. The other tested methods and area decompositions often yield a shorter flight path, however, despite extensive adjustments to the algorithms they never came to handle all cases in a satisfactory manner. These methods may also generate any kind of turn at any time, including turns of nearly 180 degrees. These turns can lead to an airplane missing the intended flight path and thus missing to scan the intended area properly. Area decomposition proves to be really effective only when the area has many protrusions that stick out in different directions, think of a starfish shape. In these cases the side to side algo- rithm generate a path that has long legs over parts that are not in the search area. When the area is decomposed the algorithm starts with, for example, one arm of the starfish at a time and then search the rest of the arms and body in turn. 

    Download full text (pdf)
    Search path generation with UAV applications using approximate convex decomposition
  • 3792.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed Loop Identification of the Physical Parameters of an Industrial Robot2001In: Proceedings of the Third Conference on Computer Science and Systems Engineering, 2001, p. 191-198Conference paper (Other academic)
    Abstract [en]

    This paper discusses experimental identication of a flexible robot under strong feedback. Black-box models are compared with physically parameterized models. The parameters in the physical models and the blackbox models are identified from the input-output data using prediction error methods. We also investigate the importance of noise models when performing identication under strong feedback. The robot that we use is a commercial ABB robot, IRB 1400.

  • 3793.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed Loop Identification of the Physical Parameters of an Industrial Robot2001In: Proceedings of the 32nd International Symposium on Robotics, 2001Conference paper (Refereed)
    Abstract [en]

    This paper discusses experimental identication of a flexible robot under strong feedback. Black-box models are compared with physically parameterized models. The parameters in the physical models and the blackbox models are identified from the input-output data using prediction error methods. We also investigate the importance of noise models when performing identification under strong feedback. The robot that we use is a commercial ABB robot, IRB 1400.

  • 3794.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed Loop Identification of the Physical Parameters of an Industrial Robot2000Report (Other academic)
    Abstract [en]

    This paper discusses experimental identication of a flexible robot under strong feedback. Black-box models are compared with physically parameterized models. The parameters in the physical models and the blackbox models are identified from the input-output data using prediction error methods. We also investigate the importance of noise models when performing identication under strong feedback. The robot that we use is a commercial ABB robot, IRB 1400.

    Download full text (pdf)
    FULLTEXT01
  • 3795.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Identification, Diagnosis, and Control of a Flexible Robot Arm2002Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The most important factors in manufacturing are quality, cost, and productivity. The trend is towards lighter robots with increased mechanical flexibilities, and therefore there is a need to include the flexibilities in the robot models to obtain good performance of the robot. The core theme in this thesis is modeling and identification of the physical parameters of an ABB IRB 1400 industrial robot. The approximation made is that the robot arm can be described using a finite number of masses connected by springs and dampers. It has been found that a three-mass model gives a reasonably good description of the robot when moving around axis one. The physical parameters of this model are identified using off-line and on-line algorithms. The algorithms are based on prediction error methods. For the on-line identication the Matlab System Identifiation Toolbox is used. For the on-line identication the algorithm used is a modified version of a recursive prediction error method to cope with continuous time models. The models are then used in diagnosis and control. Two ways of doing diagnosis using on-line identification are investigated. Estimating some of the physical parameters of the robot arm recursively makes it possible to monitor important aspects of the system such as friction and load. LQG control of the flexible robot arm is also studied with the aim of good disturbance rejection. Aspects that have been studied are unstable regulators and the use of accelerometers.

  • 3796.
    Östring, Måns
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On Modeling, Fault Detection and Fault Isolation of Valve and Pipe System2000Report (Other academic)
    Abstract [en]

    Valve and pipe systems are used in many areas. Often there is redundancy in the system. If one valve breaks it may be possible to lead the gas (or fluid) another way. To do this automatically we have to be able to detect and isolate faults. In this report, we show a way to use discrete event dynamical system models for analyzing where to put sensors in a valve and pipe system.

    Download full text (pdf)
    FULLTEXT01
  • 3797.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Recursive Identification of Physical Parameters in a Flexible Robot Arm2002Report (Other academic)
    Abstract [en]

    Recursive identification of physically parameterized models of continuous time systems is considered. As an example a model of a single link flexible robot arm is considered. The aim of the identification is to generate on-line estimates of physical parameters that can be used for, e.g., diagnosis purposes. For evaluation the algorithm is applied to data from an industrial robot, and three important parameters are identified using only measurements of the motor angle.

    Download full text (pdf)
    FULLTEXT01
  • 3798.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed-Loop Identification of an Industrial Robot Containing Flexibilities2001Report (Other academic)
    Abstract [en]

    Closed-loop identification of an industrial robot of the type ABB IRB 1400 is considered. Data are collected when the robot is subject to feedback control and moving around axis one. Both black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities. It is found that a model consisting of three-masses connected by springs and dampers gives a good description of the dynamics of the robot.

    Download full text (pdf)
    FULLTEXT01
  • 3799.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Closed-Loop Identification of an Industrial Robot Containing Flexibilities2003In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 11, no 3, p. 291-300Article in journal (Refereed)
    Abstract [en]

    Closed-loop identification of an industrial robot of the type ABB IRB 1400 is considered. Data are collected when the robot is subject to feedback control and moving around axis one. Both black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities. It is found that a model consisting of three-masses connected by springs and dampers gives a good description of the dynamics of the robot.

  • 3800.
    Östring, Måns
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Tjärnström, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Norrlöf, Mikael
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Modeling of Industrial Robot for Identification, Monitoring and Control2002In: Proceedings of the 2002 International Symposium on Advanced Control of Industrial Processes, 2002Conference paper (Refereed)
    Abstract [en]

    In this paper we study the problem of a modeling, identifying, and monitoring an industrial robot. We start by showing how a robot can be modeled in increasing degree of accuracy using high end tools such as MathModelica. This model can be transformed semi-automatically into a minimal state-space form which in turn can be used for identification. Moreover, the physically connected equations can be identified recursively, making it possible to monitor critical parts of the robot. When attached to a well trimmed detection scheme this provides a big help for operators, who easily can track problems with the process.

7374757677 3751 - 3800 of 3807
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf