Learning open-loop from closed-loop control
نویسنده
چکیده
This paper explores an evolution from closed-loop control to open-loop control for a planar manipula-tor. A reinforcement learning strategy is used to learn the open-loop commands from the closed-loop control. The goal is to produce a motion using purely open-loop control strategy, thereby eliminating the need for inter-link communication and on-line control computations. Initially closed loop control is used to ensure that the target is reached. The integral of the transient error is used to modify the controller gains. After repeated iterations of the same motion, the controller learns the gains to use so that the motion is open-loop. Simulation and experiments are performed to demonstrate the process.
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