TY  - JOUR
T1  - Impact of Artificial Neural Network for DC Motor Speed Control Over the
Conventional Controller
AU - Rashid Zaidan, Majeed 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 21
SP  - 9156
EP  - 9163
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.9156.9163
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.9156.9163
KW  - PI
KW  -ANN
KW  -DCM
KW  -GA
KW  -FL
KW  -AC
KW  -DC
KW  -AI
AB  - DC motors are proven enhanced performance while it used in different applications where accurate
speed control is demanded. This study emphasises to deploy artificial neural controller for accurate and rapid
control of speed. A comparative approach is made to prove the strength of ANN controller over Proportional
Integral (PI) controller. MATLAB ANN toolbox and Simulink library is used to emulate the paradigm.
Observations are made base on experimental system and the same is revealed more rapid response to speed
fluctuation is made by ANN controller under different load circumstances. Neural network is designed to ensure
perfect speed regulation after it fed by reference speed and other electrical parameters such as voltage and
armature current. Moderated error is detected at ANN controllers of 1e-7 and 8 after 5000 epics of training
process.
ER  -