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Jeff Borggaard (Virginia Tech)27/02/2025, 11:00All talksInvited lecture
We develop and present a range of feedback control laws for the fluidic pinball control problem. This control problem seeks to control the vortex shedding behind three cylinders where cylinder rotation is the actuation mechanism. This benchmark problem has been used to demonstrate several machine learning control strategies. In this talk, we present an approach that uses interpolatory model...
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Jan Heiland (TU Ilmenau)27/02/2025, 11:20All talksInvited lecture
Polytopic autoencoders provide low-dimensional parametrizations of states in a polytope. For nonlinear PDEs, this is readily applied to low-dimensional linear parameter-varying (LPV) approximations as they have been exploited for efficient nonlinear controller design via series expansions of the solution to the state-dependent Riccati equation. In this work, we develop a polytopic autoencoder...
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Attila Karsai (TU Berlin)27/02/2025, 11:40All talksInvited lecture
Dynamical systems can be used to model a broad class of physical processes, and conservation laws give rise to system properties like passivity or port-Hamiltonian structure. An important problem in practical applications is to steer dynamical systems to prescribed target states, and feedback controllers provide a powerful tool to do so. However, controllers designed using classical methods do...
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