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Balancing based model reduction for structured index-2 unstable descriptor systems with application to flow control
Author(s) -
Mohammed Forhad Uddin,
Jens Saak,
Peter Benner
Publication year - 2016
Publication title -
numerical algebra control and optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.303
H-Index - 20
eISSN - 2155-3289
pISSN - 2155-3297
DOI - 10.3934/naco.2016.6.1
Subject(s) - control theory (sociology) , reduction (mathematics) , discretization , linear quadratic gaussian control , flow (mathematics) , mathematics , controller (irrigation) , flow control (data) , lyapunov equation , lyapunov function , truncation (statistics) , optimal control , computer science , mathematical optimization , control (management) , lyapunov exponent , mathematical analysis , nonlinear system , computer network , physics , statistics , quantum mechanics , chaotic , agronomy , biology , geometry , artificial intelligence
Stabilizing a flow around an unstable equilibrium is a typical problem in flow control. Model-based designed of modern controllers like LQR/LQG or $H_\infty$ compensators is often limited by the large-scale of the discretized flow models. Therefore, model reduction is usually needed before designing such a controller. Here we suggest an approach based on applying balanced truncation for unstable systems to the linearized flow equations usually used for compensator design. For this purpose, we modify the ADI iteration for Lyapunov equations to deal with the index-2 structure of the underlying descriptor system efficiently in an implicit way. The resulting algorithm is tested for model reduction and control design of a linearized Navier-Stokes system describing von Kármán vortex shedding.

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