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  • 1.
    Irshad, Yasir
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Physics.
    On some continuous-time modeling and estimation problems for control and communication2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The scope of the thesis is to estimate the parameters of continuous-time models used within control and communication from sampled data with high accuracy and in a computationally efficient way.In the thesis, continuous-time models of systems controlled in a networked environment, errors-in-variables systems, stochastic closed-loop systems, and wireless channels are considered. The parameters of a transfer function based model for the process in a networked control system are estimated by a covariance function based approach relying upon the second order statistical properties of input and output signals. Some other approaches for estimating the parameters of continuous-time models for processes in networked environments are also considered. The multiple input multiple output errors-in-variables problem is solved by means of a covariance matching algorithm. An analysis of a covariance matching method for single input single output errors-in-variables system identification is also presented. The parameters of continuous-time autoregressive exogenous models are estimated from closed-loop filtered data, where the controllers in the closed-loop are of proportional and proportional integral type, and where the closed-loop also contains a time-delay. A stochastic differential equation is derived for Jakes's wireless channel model, describing the dynamics of a scattered electric field with the moving receiver incorporating a Doppler shift.

  • 2.
    Irshad, Yasir
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Some estimation concepts applied to networked control systemsManuscript (preprint) (Other academic)
  • 3.
    Irshad, Yasir
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Some problems of modeling and parameter estimation in continous-time for control and communication2011Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Stochastic system identification is of great interest in the areas of control and communication. In stochastic system identification, a model of a dynamic system is determined based on given inputs and received outputs from the system, where stochastic uncertainties are also involved. The scope of the report is to consider continuous-time models used within control and communication and to estimate the model parameters from sampled data with high accuracy in a computational efficient way. Continuous-time models of systems controlled in a networked environment, stochastic closed-loop systems, and wireless channels are considered. The parameters of a transfer function based model for the process in a networked control system are first estimated by a covariance function based approach, relying upon the second order statistical properties of the output signal. Some other approaches for estimating the parameters of continuous-time models for processes in networked environments are also considered. Further, the parameters of continuous-time autoregressive exogenous models are estimated from closed-loop filtered data, where the controllers in the closed-loop are of proportional and proportional integral type, and where the closed-loop also contains a time-delay. Moreover, a stochastic differential equation is derived for Jakes's wireless channel model, describing the dynamics of a scattered electric field with the moving receiver incorporating a Doppler shift.

  • 4.
    Irshad, Yasir
    et al.
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Mossberg, Magnus
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    A comparison of estimation concepts applied to networked control systems2012In: 19th International Conference on Systems, Signals and Image Processing (IWSSIP), 2012, Piscataway: IEEE Press, 2012, p. 114-117Conference paper (Refereed)
    Abstract [en]

    A continuous-time description of networked control systems is considered and the parameters are estimated. The discrete-time description is time-varying due to the random time-delays in the wireless links and therefore difficult to work with. Off-line as well as on-line situations are considered for parameter estimation. In the off-line situation, a linear regression is formed and then the parameters are estimated by the least squares method. In the on-line situation, the estimates of the parameters are recursively updated for each time instance. A comparative study of two different parameter estimation approaches is presented. In the first approach, the parameters are estimated by a simple linear regression. In the second approach, transformation of the differentiation operator to another casual and stable linear operator is made in linear regression to estimate the parameters. A numerical study of these approaches is also presented for comparison.

  • 5.
    Irshad, Yasir
    et al.
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Mossberg, Magnus
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Wireless channel modeling based on stochastic differential equations2011Other (Other academic)
  • 6.
    Irshad, Yasir
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Physics. Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Mossberg, Magnus
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Söderström, Torsten
    Division of Systems and Control, Department of Information Technology, Uppsala University.
    System identification in a networked environment using second order statistical properties2013In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 49, no 2, p. 652-659Article in journal (Refereed)
    Abstract [en]

    System identification for networked control is considered. Due to the time-delays in the network, it can be difficult to work with a discrete-time model and a continuous-time model is therefore chosen. A covariance function based method that relies on the second order statistical properties of the output signal, where it is assumed that the input signal samples are from a discrete-time white noise sequence, is proposed for estimating the parameters. The method is easy to use since the actual time instants when new input signal levels are applied at the actuator do not have to be known. An analysis of the networked system and the effects of the time-delays is made, and the results of the analysis motivate and support the chosen approach. Numerical studies indicate that the method is robust to randomly distributed time-delays, packet drop-outs, and additive measurement noise.

  • 7.
    Mossberg, Magnus
    et al.
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Irshad, Yasir
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    A stochastic differential equation for wireless channels based on Jakes' model with time-varying phases2009Conference paper (Refereed)
  • 8.
    Mossberg, Magnus
    et al.
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Irshad, Yasir
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Closed-loop identification of P- and PI-controlled time delayed stochastic systemsManuscript (preprint) (Other academic)
  • 9.
    Mossberg, Magnus
    et al.
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Irshad, Yasir
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Physics.
    Closed-loop Identification of Stochastic Models from Filtered Data2008Conference paper (Refereed)
  • 10.
    Mossberg, Magnus
    et al.
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Irshad, Yasir
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Söderström, T
    A covariance function based approach to networked system identification2010Conference paper (Refereed)
  • 11.
    Söderström, Torsten
    et al.
    Uppsala University.
    Irshad, Yasir
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Mossberg, Magnus
    Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
    Zheng, Wei Xing
    University of Western Sydney.
    Accuracy analysis of a covariance matching method for continuous-time errors-in-variables system identification2012In: : IFAC Proceedings Volumes, Elsevier, 2012, Vol. 45, p. 1383-1388Conference paper (Refereed)
  • 12.
    Söderström, Torsten
    et al.
    Uppsala University.
    Irshad, Yasir
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Physics (from 2013).
    Mossberg, Magnus
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Physics (from 2013).
    Zheng, Wei Xing
    University of Western Sydney.
    On the accuracy of a covariance matching method for continuous-time errors-in-variables identification2013In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 49, no 10, p. 2982-2993Article in journal (Refereed)
1 - 12 of 12
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