フィードバック誤差学習を用いたオンライン倒立振子制御(一般,ニューロハードウェア,一般)

概要

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This paper presents an application of the feedback error learning technique for online control of an inverted pendulum system which has uncertain friction nonlinearity. In order to make possible online adaptive learning system, the preliminary training and the scaling factor for the neural network and two stages learning scheme are introduced. After some learning cycles (or epochs), responses of the plant show the minimum values that the feedback error learning scheme acts as an adaptive controller to minimize the control error. This means that the neural network acquires the inverse dynamic model of the plant through learning and then compensates the nonlinearity of the plant. The phase relationship between the output of the conventional feedback controller and the neural network is clarified. It is also shown that this control system works well for a step reference signal after learning.
社団法人電子情報通信学会の論文
2007-11-11