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Adaptive reinforcement learning system for linearization control

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2 Author(s)
Kao-Shing Hwang ; Dept. of Electr. Eng., Nat. Chung Cheng Univ., Tainan, Taiwan ; Horag-Jen Chao

A linearization scheme is proposed to demonstrate how a neural network scheme learns to linearize a system without any identification. The process occurs within an evaluator and a controller, which communicate with each other through reinforcement signals. From simulation results, the proposed learning scheme notably surpasses the conventional neural network approaches

Published in:

IEEE Transactions on Industrial Electronics  (Volume:47 ,  Issue: 5 )