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Robustness guarantees for linear control designs with an estimated nonlinear model error model
Author(s) -
Glad S. T.,
Helmersson A.,
Ljung L.
Publication year - 2004
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.926
Subject(s) - robustness (evolution) , nonlinear system , control theory (sociology) , linear model , computer science , linear system , affine transformation , robust control , errors in variables models , system identification , mathematical optimization , mathematics , control (management) , data modeling , artificial intelligence , mathematical analysis , biochemistry , chemistry , physics , quantum mechanics , machine learning , database , pure mathematics , gene
Much attention in robust identification and control has been focused on linear low order models approximating high order linear systems. We consider the more realistic situation with a linear model approximating a nonlinear system. We describe how a nonlinear model error model can be developed, that allows a complete linear design process that results in a closed loop system with performance robustness guarantees (in terms of gain from disturbance to output) against the nonlinear error. Clearly the design can be successful only if the linear model is a reasonably good approximation of the system. A particular aspect of the design process is to define a workable definition of ‘practical stability’ for robust control design, with possible non‐linear model errors. We use affine norms for that purpose. Copyright © 2004 John Wiley & Sons, Ltd.