| contributor author | Xiaoqiu Li | |
| contributor author | Stephen Yurkovich | |
| date accessioned | 2017-05-09T00:02:05Z | |
| date available | 2017-05-09T00:02:05Z | |
| date copyright | June, 2000 | |
| date issued | 2000 | |
| identifier issn | 0022-0434 | |
| identifier other | JDSMAA-26267#269_1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/123472 | |
| description abstract | An adaptive sliding mode control design method is proposed for discrete nonlinear systems where explicit knowledge of the system dynamics is not available. Three-layer feedforward neural networks are used as function approximators for the unknown dynamics. The control law is designed based on the outputs of the approximators, and the sliding surface is defined in terms of a stable polynomial of the system outputs. Convergence of the state trajectories into a small sliding sector is proved. The method is applied to the internal combustion (IC) engine idle speed control problem. Simulation and experimental results are provided. [S0022-0434(00)01702-0] | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Neural Network Based, Discrete Adaptive Sliding Mode Control for Idle Speed Regulation in IC Engines | |
| type | Journal Paper | |
| journal volume | 122 | |
| journal issue | 2 | |
| journal title | Journal of Dynamic Systems, Measurement, and Control | |
| identifier doi | 10.1115/1.482463 | |
| journal fristpage | 269 | |
| journal lastpage | 275 | |
| identifier eissn | 1528-9028 | |
| keywords | Sliding mode control | |
| keywords | Internal combustion engines | |
| keywords | Artificial neural networks | |
| keywords | Engines | |
| keywords | Errors | |
| keywords | System dynamics | |
| keywords | Feedforward control AND Polynomials | |
| tree | Journal of Dynamic Systems, Measurement, and Control:;2000:;volume( 122 ):;issue: 002 | |
| contenttype | Fulltext | |
