335 運動系のモデル獲得と制御(アドバンスト制御理論応用II)(OS アドバンスト制御理論応用)

概要

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This paper proposes a motion learning method for motion systems using basis function networks free from analytical formulation. Motion system has unknown nonlinearities such as variation of inertia, Coriolis's force, nonlinear electromagnetic driving characteristics and gravity that are complicated to formulate. In this study, these nonlinearities are described by basis function networks. The updating rules of the weights in the network is derived by Popov's. Hyper Stable Theory. This paper shows independence of analytical formulation for motion systems and effectiveness of the proposed motion control method by demonstrating an experiment of tracking desired trajectory in a 2-degree-of-freedom link motion system.
一般社団法人日本機械学会の論文
2001-04-20