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Q-learning used for control of AMB: reduced state definition
Březina, Tomáš ; Krejsa, Jiří
Previous work showed that stochastic strategy improved model free RL method known as Q-learning used on active magnetic bearing (AMB) model. So far the position, velocity and acceleration were used to describe the state of the system. This paper shows simplified version of controller which uses reduced state definition - position and velocity only. Furthermore the controlled initial conditions domain and its development during learning are shown.
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