2013
DOI: 10.12691/ajme-1-1-1
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Friction Effect Analysis of a DC Motor

Abstract: Precision positioning systems are fundamental components in industrial machines such as machine tools, measuring machines and semiconductor manufacturing systems. The performance of the machines depends on the positioning systems. For precise positioning are often used DC motors. The paper deals with experimental method of DC motor friction identification. The aim of the paper is determining of suitable way of DC motor friction modeling. At first the basic static friction models are introduced and linear mathe… Show more

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Cited by 48 publications
(21 citation statements)
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References 9 publications
(10 reference statements)
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“…Hence, the kinematic analysis conducted shows that the thumb can be defined as three links having four DOF, whereas the arrow and middle finger can be defined as four links having five DOF's. This structure enables grasping, holding and squeezing to be performed by a human [21].…”
Section: Flex Sensor Based Sensor Systemmentioning
confidence: 99%
“…Hence, the kinematic analysis conducted shows that the thumb can be defined as three links having four DOF, whereas the arrow and middle finger can be defined as four links having five DOF's. This structure enables grasping, holding and squeezing to be performed by a human [21].…”
Section: Flex Sensor Based Sensor Systemmentioning
confidence: 99%
“…It consists of both electrical and mechanical elements [11]. Figure 2 shows a simplified DC motor model, and Figure 3 shows a block diagram for a DC motor that is obtained by using Laplace Transform.…”
Section: Motor Mathematical Modelmentioning
confidence: 99%
“…In the case of ideal velocity tracking in both internal loops, the dynamic navigation control becomes a pure kinematic control task [2,9,17,18]. Dynamic properties of mobile robot, such as its moment of inertia or friction represents an undesirable impact on its movement properties [6,7,10,19]. The non-ideal reference velocities tracking results into a position error, that is subject of minimization for navigation control [3,4,8].…”
Section: Introductionmentioning
confidence: 99%
“…In order to achieve relevant training data, the mathematical model that forms the base of simulation model in addition to general dynamic properties includes dynamical effects of actuators and viscous friction [7,19]. The training data are measured in simulation experiment on a single wheel subsystem and trained neural networks are used in direct-inverse neural control structure for internal wheel velocity tracking loops.…”
Section: Introductionmentioning
confidence: 99%