データ同化を用いた確率的パラメータ同定の逐次化とその実験検証

抄録

Accurate identification of minimum set of dynamics parameters is required for high-precision and high-speed motion control. However, since there is generally some difference between the model used for control system design and the dynamics of the actual target system, the conventional parameter identification method cannot provide an appropriate model for use in control system design. To address this problem, we have proposed a method to obtain parameters suitable for use in control system design by considering stochastic variables. In addition, we have proposed a method to obtain the probability distribution of the parameters and to update them recursively by using the concept of data assimilation. In this study, the effectiveness of our proposed stochastic parameter identification and its sequentialization is verified using a planar 3-link manipulator.