Uncertainty identification for a nominal LPV vehicle model based on experimental data

Rödönyi, Gábor and Bokor, József (2005) Uncertainty identification for a nominal LPV vehicle model based on experimental data. In: CDCâ��05-ECC'05. Proceedings of the 44th IEEE conference on decision and control, and the European control conference 2005. Seville, 2005..

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In this paper a practical method is presented for modelling uncertainty of a nominal linear parametervarying (LPV) vehicle model. The aim with the uncertainty model is to bound the nominal model-error and satisfy robust stability and performance objectives during robust control design. Existing frequency-domain model-validation methods are applied to perform the first aim. The linear fractional uncertainty structure and the distribution of nominal modelerror among the uncertainty blocks and disturbances are chosen to perform the second aim. The paper is motivated by the problem of steering a vehicle by alternately braking the front wheels in emergency situations. The identification is performed on real experiment data. The method and the results are demonstrated on a yaw-rate tracking problem and mu-controller design on constant scheduling variable of the LPV model. Using the proposed algorithm, on the supposition that nominal model error remains below the bound estimated from the validation data set, an unfalsified model is constructed ffor robust control guaranteeing robust performance against worstcase uncertainty and disturbance.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: mu-synthesis, uncertainty modeling
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Systems and Control Lab
Depositing User: Eszter Nagy
Date Deposited: 11 Dec 2012 15:17
Last Modified: 11 Dec 2012 15:17
URI: https://eprints.sztaki.hu/id/eprint/3857

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