| contributor author | Anthony Tzes | |
| contributor author | Pei-Yuan Peng | |
| date accessioned | 2017-05-08T23:53:00Z | |
| date available | 2017-05-08T23:53:00Z | |
| date copyright | June, 1997 | |
| date issued | 1997 | |
| identifier issn | 0022-0434 | |
| identifier other | JDSMAA-26234#312_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/118437 | |
| description abstract | The application of a fuzzy neural network controller for compensating the effects induced by the friction in a DC-motor micromaneuvering system is considered in this article. A back-propagation neural network is employed to decrease the effects of the system nonlinearities. The input vector to the neural network controller consists of the time history of the motor angular shaft velocity within a prespecified time window. A fuzzy cell space controller supervises the overall scheme and reduces the amplitude and repetitions of control switchings. Simulation studies are presented to indicate the effectiveness of the proposed algorithm. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Fuzzy Neural Network Control for DC-Motor Micromaneuvering | |
| type | Journal Paper | |
| journal volume | 119 | |
| journal issue | 2 | |
| journal title | Journal of Dynamic Systems, Measurement, and Control | |
| identifier doi | 10.1115/1.2801254 | |
| journal fristpage | 312 | |
| journal lastpage | 315 | |
| identifier eissn | 1528-9028 | |
| keywords | Engines | |
| keywords | Fuzzy neural nets | |
| keywords | Control equipment | |
| keywords | Artificial neural networks | |
| keywords | Friction | |
| keywords | Simulation AND Algorithms | |
| tree | Journal of Dynamic Systems, Measurement, and Control:;1997:;volume( 119 ):;issue: 002 | |
| contenttype | Fulltext | |
