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  • 1.
    Falkeborn, Rikard
    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.
    A Decomposition Algorithm for KYP-SDPs2012In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 18, no 3, p. 249-256Article in journal (Refereed)
    Abstract [en]

    In this paper, a structure exploiting algorithm for semidefinite programs derived from the Kalmatz-Yakubovich-Popov lemma, where some of the constraints appear as complicating constraints is presented. A decomposition algorithm is proposed, where the structure of the problem can be utilized. In a numerical example, where a controller that minimizes the stun of the H-2-norm and the H-infinity-norm is designed, the algorithm, is shown to be faster than SeDuMi and the special purpose solver KYPD.

  • 2.
    Hjalmarsson, Håkan
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gevers, Michel
    Université Catholique de Louvain, Belgium.
    Gunnarsson, Svante
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Model-free Tuning of a Robust Regulator for a Flexible Transmission System1995In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 1, no 2, p. 148-156Article in journal (Refereed)
    Abstract [en]

    Recently, a data-driven model-free iterative control design method has been proposed [Hjalmarsson et al., Proc. 33rd IEEE CDC, Orlando, FL, 1994, 1735–1740]. This design method works directly with closed loop data from the plant and iteratively improves the pelformance. This contribution reports a simulation study of this method when applied to a flexible transmission system. The system is characterised by load dependent dynamics and certain performance specifications have to be satisfied for three different load cases. These specifications cannot be translated into a specific control criterion a priori. However, by adaptively changing the design criterion it is shown that it is possible to tune the criterion so as to eventually obtain the desired closed loop performance for all three load cases with the same controller. The new concepts of synthetic noise and time delays are shown to be valuable tools when tuning the criterion.

  • 3.
    Kinnaert, M
    et al.
    Linkoping Univ, Dept Elect Engn, SE-58183 Linkoping, Sweden IRISA CNRS, F-35042 Rennes, France.
    Nyberg, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Basseville, M
    Linkoping Univ, Dept Elect Engn, SE-58183 Linkoping, Sweden IRISA CNRS, F-35042 Rennes, France.
    Discussion on: 'On fault detectability and isolability' by M. Basseville2001In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 7, no 6, p. 638-641Other (Other academic)
  • 4.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Estimating Linear Time-Invariant Models of Nonlinear Time-Varying Systems2001In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 7, no 2-3, p. 203-219Article in journal (Refereed)
    Abstract [en]

    The standard machinery for system identification of linear time-invariant (LTI) models delivers a nominal model and a confidence (uncertainty) region around it, based on (second order moment) residual analysis and covariance estimation. In most cases this gives an uncertainty region that tends to zero as more and more data become available, even if the true system is nonlinear and/or time-varying. In this paper, the reasons for this are displayed, and a characterization of the limit LTI model is gh,en under quite general conditions. Various ways are discussed, and tested, to obtain a more realistic limiting model, with uncertainty. These should reflect the distance to the true possibly nonlinear, time-varying system, and also form a reliable basis for robust LTI control design.

  • 5.
    Ljung, Lennart
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Automatic Control.
    Boaghe, O.M.
    Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
    Billings, S.A.
    Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
    Letters to the editor on the paper 'dynamic wavelet and equivalent models' by O.M. Boaghe and S.A. Billings2000In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 6, no 3, p. 295-296p. 295-296Article in journal (Other academic)
  • 6.
    Ljung, Lennart
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hjalmarsson, Hakan
    Royal Institute of Technology, Sweden.
    Ohlsson, Henrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Four Encounters with System Identification2011In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 17, no 5-6, p. 449-471Article in journal (Refereed)
    Abstract [en]

    Model-based engineering becomes more and more important in industrial practice. System identification is a vital technology for producing the necessary models, and has been an active area of research and applications in the automatic control community during half a century. At the same time, increasing demands require the area to constantly develop and sharpen its tools. This paper deals with how system identification does that by amalgamating concepts, features and methods from other fields. It describes encounters with four areas in systems theory and engineering: Networked Systems, Particle Filtering Techniques, Sparsity and Compressed Sensing, and Machine Learning. The impacts on System Identification methodology by these encounters are described and illustrated.

  • 7.
    Ljung, Lennart
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Reinelt, Wolfgang
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Robust Control of Identified Models with Mixed Parametric and Non-Parametric Uncertainties2003In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 9, no 4, p. 373-380Article in journal (Refereed)
    Abstract [en]

    A framework for identification oriented robust controller design is developed. The model is identified from open-loop i/o-data and contains parametric uncertainties as well as an additive and norm-bounded error. The set of all robustly stabilising controllers, that additionally guarantee robust performance is characterised by a system of second order cones, which can be efficiently solved by interior point algorithms.

  • 8.
    McKelvey, Tomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Discussion on "On the Use of Minimal Parametrizations in Multivariable ARMAX Identification" by R.P. Guidorzi1998In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 4, p. 93-98Article in journal (Refereed)
    Abstract [en]

    When performing practical identication the structural issue often cannot be neglected since the conditioning of the parameterization influence the convergence of the optimization. Solutions are to carefully monitor the conditioning of the associated LS problem or to use alternative parametrizations (minimal or non-minimal) which give better conditioning.

  • 9.
    Panteley, Elena
    et al.
    INRIA Rhone Alpes, France.
    Loria, Antonio
    CNRS UMR 5528, France.
    Sokolov, Alexei
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Global Uniform Asymptotic Stability of Cascaded Nonlinear Non-Autonomous Systems1999In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 5, no 1, p. 107-115Article in journal (Refereed)
    Abstract [en]

    In this paper, we deal with the stability analysis problem of cascaded non-autonomous non-linear systems. In particular, we answer to the following questions: (i) What happens with the solutions of a time-varying non-linear system which is globally uniformly stable (GUS), when it is perturbed by the output of a globally exponentially stable (GES) system, in particular, when both systems form a cascade? (ii) If a time-varying non-linear system is globally uniformly asymptotically stable (GUAS), is this stability properly preserved when it is perturbed by an exponentially decaying input? Our proofs are based on a standard ‘delta-epsilon’ Lyapunov analysis. Finally, we show the utility of our results by applying our theorems to the problem of stabilisation of a turbo-charged diesel engine.

  • 10.
    Svärd, Carl
    et al.
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    Nyberg, Mattias
    Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, The Institute of Technology.
    An Observer-Based Residual Generation Method for Linear Differential-Algebraic Equation Systems2009In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671Article in journal (Other academic)
    Abstract [en]

    Residual generation for linear differential-algebraic systems is considered. A new systematic method for observer-based residual generation is presented. The proposed design method places no restrictions on the system to be diagnosed. If the fault of interest can be detected in the system, the output from the design method is a residual generator in state-space form that is sensitive to the fault of interest. The method is iterative and relies only on constant matrix operations such as multiplications, null-space calculations and equivalence transformations, and thereby straightforward to implement. An illustrative numerical example is included, where the design method is applied to a nonobservable model of a robot manipulator.

  • 11.
    Tjernström, Fredrik
    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.
    Variance Properties of a Two-Step ARX Estimation Procedure2003In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 9, no 4, p. 422-430Article in journal (Refereed)
    Abstract [en]

    In this contribution, the variance properties of a two-step ARX estimation scheme are discussed. An expression for the covariance of the final low-order model is calculated and it is shown how this covariance can be minimised (at least for high-model orders). The implication of the results is that identification of the dynamics of a system can very easily be performed with standard linear least squares (two times), even if the measurement noise is heavily colored. A numerical example is included, where this two-step method gives a variance which is close (but not equal) to the Cramèr-Rao lower bound. Moreover, the point estimate of the covariance is close to the one obtained through Monte Carlo simulations.

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