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Reduced-order adaptive controllers for MHD flows using proper orthogonal decomposition

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1 Author(s)
Ravindran, S.S. ; Dept. of Math. Sci., Alabama Univ., Huntsville, AL, USA

We present a reduced-order adaptive controller design for MHD flows. Frequently, reduced-order models are derived from low-order bases computed by applying proper orthogonal decomposition (POD) on an a priori ensemble of data of ow model. This reduced-order model is then used-to derive a reduced-order controller. The approach discussed here differs from these approaches. It. uses an adaptive procedure that improves the reduced-order model by successively updating the ensemble of data. The idea is illustrated on a control problem in unsteady magneto-hydrodynamic (MHD) flows. Numerical implementations and results are provided illustrating feasibility

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Decision and Control, 2001. Proceedings of the 40th IEEE Conference on  (Volume:3 )

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