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EMISSION LINE VELOCITY FIELD OF THE MAGELLANIC IRREGULAR GALAXY NGC 4449
SASAKI MINORU,OHTANI HIROSHI,SAITO MAMORU,OHTA KOUJI,YOSHIDA MICHITOSHI,SHIMIZU TASUHlRO,KOYANO HISASHI,KOSUGI GEORGE,AOKI KENTARO,SASAKI TOSHIYUKI The Korean Astronomical Society 1996 Journal of The Korean Astronomical Society Vol.29 No.suppl1
The imaging spectroscopic observations of the Magellanic irregular galaxy NGC 4449 were made to show the detailed kinematic structure of the galaxy. Many filamentary structures and Several bubble-like structures are recognized in a 3D data cube of H$\alpha$ emission line. Velocity field shows the kpc-scale mosaic structure and counter- rotation of ionized gas.
Two-Degree-of-Freedom Control of a Stacker Crane
Minoru Sasaki,Toshimi Shimizu,Kengo Suzuki,Shingo Naito,Satoshi Ito 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
This paper presents a motion control of a stacker crane applying a two-degree-of-freedom control. The two-degree-of-freedom control system consists of a feed forward controller based on an inverse system and a feed backcontroller with suppressing the vibration effectively and stabilizing. Feedback control of the motion of the stacker crane is derived by considering the time rate of change of the total energy of the system. This approach has the advantage overthe conventional methods in the respect that it allows one to deal directly with the system’s partial differential equations without resorting to approximations. The paper concludes by presenting some numerical results and experimental results for a special case using a proposed control system. These results show that the two-degree-of-freedom control system can realize faster and precise tracking control of the flexible stacker crane system.
Self-Tuning Control of a Two-Link Flexible Manipulator using Neural Networks
Minoru Sasaki,Akihiro Asai,Toshimi Shimizu,Satoshi Ito(편집자) 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, a self-tuning control of a two-link flexible manipulator using neural networks is presented. The neural networks learn the gains of PI controllers for the flexible manipulator. Numerical results show that this presented neural network control system can suppress the vibration of the flexible manipulator and track the desired joint angles.Simulation results show that the self-tuning control system using neural network can be used effectively for the position control of the two-link flexible manipulator.