Minimum order linear system identification and parameter estimation with application

Erdoğan, Onur Cem
Design, control, and investigation of complex systems require a tool to understand and model system behavior. This tool is the system identification, which convert the system response to a mathematical formulation. During the identification phase, the utilized model is important to convey system behavior. In this study, a number of minimum order and non-parametric system identification algorithms are implemented for the identification of linear time invariant mechanical systems. For this purpose, impulse response determination methods are investigated to obtain system behavior. State space modeling and special models used in the identification process of physical systems are investigated. Two system realization algorithms implementing minimum order non-parametric linear system identification are presented. A transformation based method for the extraction of physical system parameters from a real system model is represented. The suggested methods are implemented on both simulation and test data for different system models to investigate their effectiveness and performance.


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Citation Formats
O. C. Erdoğan, “Minimum order linear system identification and parameter estimation with application,” M.S. - Master of Science, Middle East Technical University, 2014.