On control-specific derivation of affine Takagi-Sugeno models from physical models: Assessment criteria and modeling procedure

Models are commonly derived and their performance is assessed wrt. minimal prediction error on a closed data set. However, if no perfect model can be used, the degrees of freedom in modeling should be used to adjust the model to application-specific metrics. For model-based controller design, contro...

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Bibliographic Details
Published in:Computational Intelligence in Control and Automation (CICA) pp. 23 - 30
Main Authors: Kroll, A., Durrbaum, A.
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2011
Subjects:
Analytical models
Controllability
Mathematical model
Predictive models
Stability criteria
ISBN:9781424499021, 142449902X
ISSN:2328-1448
Online Access:Get full text
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Summary:Models are commonly derived and their performance is assessed wrt. minimal prediction error on a closed data set. However, if no perfect model can be used, the degrees of freedom in modeling should be used to adjust the model to application-specific metrics. For model-based controller design, control-oriented performance metrics (e.g. performance wrt. to control-critical properties) are important, but not primarily prediction (i.e. prognosis- and simulation-oriented) ones. This motivates the derivation of control-specific models. The contribution introduces structured and quantitative measures on "model suitability for control" for the class of affine dynamic Takagi-Sugeno models. A method is suggested that derives control-specific dynamic models from a physical model given as a set of nonlinear differential equations. Within a case study, the proposed method demonstrates its significance: Using control-specific models improves control performance metrics such as set-point tracking quality, stability region and energy efficiency. Nonlinear dynamic modeling, Takagi-Sugeno systems, modeling for control performance metrics such as set-point tracking quality, stability region and energy efficiency.
ISBN:9781424499021
142449902X
ISSN:2328-1448
DOI:10.1109/CICA.2011.5945746