| dc.contributor.author | Soumana, R. A. | |
| dc.contributor.author | Saulo, M. J. | |
| dc.contributor.author | Muriithi, Christopher M. | |
| dc.date.accessioned | 2022-03-12T09:50:54Z | |
| dc.date.available | 2022-03-12T09:50:54Z | |
| dc.date.issued | 2022-02 | |
| dc.identifier.citation | 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT) | en_US |
| dc.identifier.uri | https://ieeexplore.ieee.org/document/9716556 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/5536 | |
| dc.description.abstract | The dynamic behavior of a PID-type fuzzy logic control depends on the appropriate choice of its scaling factors. Fixed scaling factors cannot provide adequate control performance under a wide range of operating conditions. This paper proposes a control strategy for separately excited dc motor (SEDCM) speed control based on fuzzy logic and neural networks. The function of the neural networks is to adapt the scaling factors at the inputs and output of the fuzzy logic controller. Using MATLAB/Simulink, the performance of the proposed controller is highlighted in comparison with anti-windup proportional-integral (PI) and sliding mode controllers under variable speed reference, disturbances, and armature resistance variation. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.subject | Separately Excited DC Motor, Speed Control, Fuzzy Logic Control, Artificial Neural Networks, Scaling Factors. | en_US |
| dc.title | Enhanced Speed Control of Separately Excited DC Motor Using Fuzzy-Neural Networks Controller | en_US |
| dc.type | Article | en_US |
