The phenomenon of magnetic levitation represents an interesting challenge from a control perspective due to its nonlinearity. Through computer simulated control environments we compared the results of using classic PID modeled control and a control agent taught through reinforcement learning. While the latter performed marginally better in terms of transient state duration and robustness, PID control still offered a stable and accurate result while proving much simpler to achieve.
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