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국태용 木浦大學校 工業技術硏究所 1993 工業技術硏究誌 Vol.3 No.-
An iterative learning scheme comprising a unique feedforward learning controller and a linear feedback controller is presented. In the feedback loop, the fixed-gain controller provides a stable open neighborhood along a desired trajectory. In the feedforward path, on th other hand, a learning control strategy is exploited to predict the desired actuator torques. It is shown that the predicted actuator torque converges to the desired one as the iteration number increases. The convergence is established based on the Lyapunov stability theory. The proposed learning scheme is structurely simple and computationaly efficient. Moreover, it posesses two major advantages : the ability to reject unknown deterministic disturbances and the ability to adapt itself to the unknown system parameters.