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Control in machine learning

Priv. Doz. Dr. Markus Abel

We present a new approach for the control of systems
with complex dynamics: In order to determine the optimal
control function we apply a machine learning algorithm, genetic
programming. With this method and a clever-chosen cost function
we are able to determine fully nonlinear control laws in
a systematic way. We apply our algorithm to a turbulent mixing layer,
and the Lorenz system in a periodic state with the goal to
achieve maximum mixing, characterized by the Lyapunov exponents of
the system. Further, we control coupled nonlinear oscillators to
hold them in a stationary state.

Date: 29.04.2014
Time: 4pm
Location: EW 731, TU Berlin, Hardenbergstr. 36, 10623 Berlin

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