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System identification in a networked environment using second order statistical properties
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.
Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering. (Matematisk modellering)
Division of Systems and Control, Department of Information Technology, Uppsala University.
2013 (English)In: Automatica, ISSN 0005-1098, Vol. 49, no 2, 652-659 p.Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
2013. Vol. 49, no 2, 652-659 p.
Keyword [en]
Networked control systems;
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kau:diva-26431DOI: 10.1016/j.automatica.2012.11.039ISI: 000315003100040OAI: oai:DiVA.org:kau-26431DiVA: diva2:606906
Available from: 2013-02-21 Created: 2013-02-21 Last updated: 2016-08-16Bibliographically approved
In thesis
1. Some problems of modeling and parameter estimation in continous-time for control and communication
Open this publication in new window or tab >>Some problems of modeling and parameter estimation in continous-time for control and communication
2011 (English)Licentiate 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.

Place, publisher, year, edition, pages
Karlstad: Karlstad University, 2011. 94 p.
Series
Karlstad University Studies, ISSN 1403-8099 ; 2011:16
Keyword
Continuous-time modeling, identification, estimation, closed-loop systems, networked control systems, wireless communication, stochastic differential equations
National Category
Physical Sciences
Research subject
Physics
Identifiers
urn:nbn:se:kau:diva-7128 (URN)978-91-7063-348-5 (ISBN)
Presentation
2011-03-30, 21A 342, Karlstad University, Karlstad, 13:15 (English)
Opponent
Supervisors
Note

Article I was still in manuscript form at the time of the defense.

Available from: 2011-03-15 Created: 2011-02-24 Last updated: 2016-08-16Bibliographically approved

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