| contributor author | Kazuhiko Takahashi | |
| contributor author | Ichiro Yamada | |
| date accessioned | 2017-05-08T23:43:43Z | |
| date available | 2017-05-08T23:43:43Z | |
| date copyright | December, 1994 | |
| date issued | 1994 | |
| identifier issn | 0022-0434 | |
| identifier other | JDSMAA-26211#792_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/113322 | |
| description abstract | This paper shows the effectiveness of a neural-network controller for controlling a flexible mechanism such as a flexible robot arm. An adaptive-type direct neural controller is formulated using state-space representation of the dynamics of the target system. The characteristics of the controller are experimentally investigated by using it to control the tip angular position of a single-link flexible arm. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Neural-Network Based Learning Control of Flexible Mechanism With Application to a Single-Link Flexible Arm | |
| type | Journal Paper | |
| journal volume | 116 | |
| journal issue | 4 | |
| journal title | Journal of Dynamic Systems, Measurement, and Control | |
| identifier doi | 10.1115/1.2899281 | |
| journal fristpage | 792 | |
| journal lastpage | 795 | |
| identifier eissn | 1528-9028 | |
| keywords | Artificial neural networks | |
| keywords | Mechanisms | |
| keywords | Control equipment | |
| keywords | Robots AND Dynamics (Mechanics) | |
| tree | Journal of Dynamic Systems, Measurement, and Control:;1994:;volume( 116 ):;issue: 004 | |
| contenttype | Fulltext | |
