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Iterative design of uncertainty models and robust controllers based on experiment data | IEEE Conference Publication | IEEE Xplore

Iterative design of uncertainty models and robust controllers based on experiment data


Abstract:

An iterative uncertainty modelling and μ-synthesis method is presented for LTI systems. In many robust control problems with complex dynamical systems, there is no a prio...Show More

Abstract:

An iterative uncertainty modelling and μ-synthesis method is presented for LTI systems. In many robust control problems with complex dynamical systems, there is no a priori information for designing a nonconservative and viable representation of the uncertainty. The goal of this paper is to provide a practical numerical method for improving the robust performance of the controlled system by designing an appropriate uncertainty model and a controller. In the proposed iterative algorithm the controller is designed by mu-synthesis and the frequency-dependent norm-bounds of the uncertainties are tuned to minimize the structured singular value with model validation constraints. Since the uncertainty model depends on the quality of the input-output measurements, therefore closed-loop experiments are involved in the iteration in order to improve the set of validation constraints. The efficiency of the method is justified by the simulation example of a vehicle steering problem.
Date of Conference: 23-26 August 2009
Date Added to IEEE Xplore: 02 April 2015
Print ISBN:978-3-9524173-9-3
Conference Location: Budapest, Hungary

References

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