Artificial intelligent speed control strategies for permanent magnet DC motor drives

El-Khouly, F.M.; Abdel-Ghaffar, A. S.; Mohammed, Arshad; Sharaf, A.Μ.

doi:10.1109/ias.1994.345476

Cited by 14 publications

(1 citation statement)

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“…he fuzzy logic controllers (FLCs) of a given process is capable of embedding, in the control strategy, the qualitative knowledge and experience of an operator or field engineer about the process [1]. Therefore, FL plays the role of a suitable 'user interface', in the task of translating designer's insight about the system into the control law, resulting in an inherently nonlinear adaptive controller, capable of outperforming other control techniques, such as model reference adaptive control and sliding mode controllers [2].…”

Section: Introductionmentioning

confidence: 99%

Speed Control For Separately Excited DC Motor Drive (SEDM) Based on Adaptive Neuro-Fuzzy Logic Controller

Mohammed¹

2013

ETJ

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This paper presents an application of Fuzzy Logic Control (FLC) in the separately excited Direct Current (DC) motor drive (SEDM) system; the controller designed according to Fuzzy Logic rules. Such that the system is fundamentally robust. These rules have capability learning, can learn and tune rapidly, even if the motor parameters are varied. The most commonly used method for the speed control of dc motor is Proportional-Integral-Derivative (PID) controller. Simulation results demonstrate that, the control algorithms Neuro-Fuzzy logic and PID, the dynamic characteristics of the SEDM (speed, torque, as well as currents) are easily observed and analyzed by the developed model. In comparison between the Neuro-fuzzy logic controller and PID controller, the FLC controller obtains better dynamic behavior and superior performance of the DC motor as well as perfect speed tracking with no overshoot, and the proposed controller provides high performance dynamic characteristics and is robust with regard to change of motor speed and external load disturbance. This paper also discusses and compares the speed control systems of SEDM using PID-controller conventional and Fuzzy Logic-controller. The entire system has been modeled using MATLAB 10a/SIMULINK toolbox.

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Section: Introductionmentioning

confidence: 99%