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On some continuous-time modeling and estimation problems for control and communication
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Physics.
2013 (English)Doctoral 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.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2013. , 208 p.
Series
Karlstad University Studies, ISSN 1403-8099 ; 2013:8
Keyword [en]
System Identification, Parameter Estimation, Continuous-time Stochastic Systems, Networked Control Systems, Errors-in-variables Systems, Wireless Channel Modeling, Closed-loop Identification
National Category
Signal Processing
Research subject
Physics
Identifiers
URN: urn:nbn:se:kau:diva-26129ISBN: 978-91-7063-482-6 (print)OAI: oai:DiVA.org:kau-26129DiVA: diva2:602546
Public defence
2013-03-26, 21A 342, Karlstads universitet, Karlstad, 13:15 (English)
Opponent
Supervisors
Note

The thesis consists of five main parts, where the first part is an introduction- Parts II-IV are based on the following articles:

Part II - Networked Control Systems

1. Y. Irshad, M. Mossberg and T. Söderström. System identification in a networkedenvironment using second order statistical properties.

A versionwithout all appendices is published as Y. Irshad, M. Mossberg and T. Söderström. System identification in a networked environment using second order statistical properties. Automatica, 49(2), pages 652–659, 2013.

Some preliminary results are also published as M. Mossberg, Y. Irshad and T. Söderström. A covariance function based approachto networked system identification. In Proc. 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems, pages 127–132, Annecy,France, September 13–14, 2010

2. Y. Irshad and M. Mossberg. Some parameters estimation methods applied tonetworked control systems.A journal submission is made. Some preliminary results are published as Y. Irshad and M. Mossberg. A comparison of estimation concepts applied to networked control systems. In Proc. 19th Int. Conf. on Systems, Signals andImage Processing, pages 120–123, Vienna, Austria, April 11–13, 2012.

Part III - Errors-in-variables Identification

3. Y. Irshad and M. Mossberg. Continuous-time covariance matching for MIMOEIV system identification. A journal submission is made.

4. T. Söderström, Y. Irshad, M. Mossberg and W. X. Zheng. On the accuracy of acovariance matching method for continuous-time EIV identification. Provisionally accepted for publication in Automatica.

Some preliminary results are published as T. Söderström, Y. Irshad, M. Mossberg, and W. X. Zheng. Accuracy analysis of a covariance matching method for continuous-time errors-in-variables system identification. In Proc. 16th IFAC Symp. System Identification, pages 1383–1388, Brussels, Belgium, July 11–13, 2012.

Part IV - Wireless Channel Modeling

5. Y. Irshad and M. Mossberg. Wireless channel modeling based on stochasticdifferential equations .Some results are published as M. Mossberg and Y. Irshad. A stochastic differential equation forwireless channelsbased on Jakes’s model with time-varying phases, In Proc. 13th IEEEDigitalSignal Processing Workshop, pages 602–605, Marco Island, FL, January4–7, 2009.

Part V - Closed-loop Identification

6. Y. Irshad and M. Mossberg. Closed-loop identification of P- and PI-controlledtime-delayed stochastic systems.Some results are published as M. Mossberg and Y. Irshad. Closed-loop identific ation of stochastic models from filtered data, In Proc. IEEE Multi-conference on Systems and Control,San Antonio, TX, September 3–5, 2008

Available from: 2013-02-28 Created: 2013-02-01 Last updated: 2013-03-06Bibliographically approved

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