System Identification and Model-Order Reduction

Summary

This chapter is dedicated to system identification and model-order reduction problems. The following items are discussed:

  • the main steps of the system identification procedure

  • concepts like ”persistence of excitation” and ”informative system identification experiment”

  • input signal design for system identification experiments

  • model-order reduction methods based on balanced truncation techniques

  • nominal plant and plant uncertainties

  • the system identification procedure is illustrated in the case of a brushless d.c. drive as well as a fuel cell.

Keywords

Nominal Plant Balance Truncation Multiplicative Uncertainty Unstructured Uncertainty Plant Uncertainty 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Mitsubishi Elevator Europe VeenendaalThe Netherlands

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