海洋ロボット用マニピュレータの学習型フィードフォワード方式による位置と力の制御

概要

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Recently, several articulated manipulators are becoming applied to the development of the ocean resources. In this paper we try to apply the Learning Feed-Forward Controller (LFFC) to the Hybrid Position and Force control system of the under water manipulator. This control system consists of a feed-forward controller based on an inverce-dynamic model of the controlled system and a feedback controller like a Proportional, Integral and Derivative controller (PID). The inverce-dynamic model expresses the values of the necessary manipulated variables to the manipulator's motion and with the feedback error learning method the output of the feedback controller tends to zero as learning proceeds. For this learning we proposed a new method in order to hasten the learning speed. Analysis for stability of control system and a series of numerical experiments or computer simulations were executed for a 2 link manipulator as an example and the results show that the new learning method succeeds in quick learning and that the control system studied in this paper achieves stable, accurate and quick response in the force and position trajectories.
社団法人日本船舶海洋工学会の論文
1993-03-29