柔軟構造物のフレキシビリティ制御 : 第5報,ニューラルネットワークを用いた柔軟材の位置・姿勢制御

概要

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This paper deals with modeling and control problems of the three joints robot handling a flexible plate in the vertical plane under gravity. The dynamics model is obtained using Hamilton's principle, and the ordinary differential equations are obtained using modal analysis. According to the desired tip position and orientation, we present an iterative algorithm to solve the inverse kinematics. The design method of the feedforward position and orientation control system is presented in two ways : ( 1 ) By solving the inverse dynamics based on the desired trajectory, we can obtain the desired torque. ( 2 ) By the use of neural networks, we can obtain the desired torque. The second method involves the use of four three-layer neural networks to reduce the feedback errors of three joints angles and the first bending vibration based on the feedback error learning method with the desired trajectories including the static bending deflection curve. We present trajectory control results for both methods. A comparison between the two methods is presented in this paper. From the simulation results, the second method, using neural networks, is useful for reducing position and orientation errors. Moreover, the second method has ability to learn and thus improve control performance against some parameter errors in the model.
一般社団法人日本機械学会の論文
1993-06-25