The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Robust Stochastic Performance Optimization

Author

Summary, in English

The problem of finding the controller that optimizes the expected H2-norm of an uncertain system is solved in closed form for a class of problems including such signal processing applications as feedforward design, channel equalization, noise cancellation etc. The method uses covariance information on model uncertainty and does therefore match information obtainable from standard system identification. The optimal controller is found by using a spectral factorization to rewrite the problem as an H2-problem for an extended system. The article puts a restrictions on where uncertain parameters enter. The need for hard bounds on parameters can then be avoided. The method also avoids the conservativeness related to designing for worst cases.

Publishing year

1993

Language

English

Publication/Series

IFAC Proceedings Volumes

Document type

Conference paper

Topic

  • Control Engineering

Conference name

12th IFAC World Congress

Conference date

1993-07-19

Conference place

Sydney, Australia

Status

Published