The paper deals with experimental friction identificat ion method of a DC motor. For precise positioning tasks a friction phenomenon plays a large problem. For this a friction has to be identified and subsequently compensated if it is important. At first the paper deals with basic friction models. In the next section the DC motor mathemat ical model is stated. The DC motor friction identificat ...

Today, DC motors is still being used globally due to their easy speed controllability. In this article, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is designed for DC motors. The main purpose of performing such task is to reduce the DC motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...

This paper presents the design and implementation of Arduino Uno based DC motor speed control system using Multilayer Neural Network controller and PID controller. A model reference structure is developed using PID control to obtain the neural controller .The artificial neural network is trained by Levenberg-Marquardt back propagation algorithm. Feed forward neural network with two hidden neuro...

This paper presents modeling of a discrete DC motor positioning using system identification. The identification of most suitable discrete model of DC motor was done by using MATLAB/Simulink. The best discrete model was determined by testing with four different sampling times. Result presented shows that the best model achieved performance of 87.79% at 55ms sampling time. Key-Words: System ident...

Brushless DC motor with high torque density and slim topology for easy loading for robot system is proposed and manufactured. Electromagnetic design is executed by equivalent magnetic circuit model and numerical analysis. Manufactured motor is tested and verified characteristics comparing with conventional BLDC motor. Keywords—Brushless DC motor, Robot joint module, Torque density, Pole/slot ratio