A fuzzy-logic concept for highly fast and accurate position control of industrial robots

2002 ◽  
Author(s):  
H.-B. Kuntze ◽  
M. Sajidman ◽  
A. Jacubasch
Keyword(s):  
Fuzzy Logic ◽  
Position Control ◽  
Industrial Robots ◽  
Accurate Position

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

Accurate Position Control for Hydraulic Servomechanisms

2019 ◽  
Author(s):  
Manuel Pencelli ◽  
Renzo Villa ◽  
Alfredo Argiolas ◽  
Gianni Ferretti ◽  
Marta Niccolini ◽  
...  
Keyword(s):  
Position Control ◽  
Accurate Position

scholarly journals Correction to: Accurate position control of shape memory alloy actuation using displacement feedback and self-sensing system

2021 ◽  
Author(s):  
Ermira Junita Abdullah ◽  
Josu Soriano ◽  
Iñaki Fernández de Bastida Garrido ◽  
Dayang Laila Abdul Majid
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Position Control ◽  
Sensing System ◽  
Accurate Position

Roboterbasierte spanende Bearbeitung*/Robot-Based Milling Operation. Machine Learning Algorithm for a model-based feed-forward torque control

2019 ◽  
Vol 109 (05) ◽  
pp. 352-357
Author(s):  
C. Brecher ◽  
L. Gründel ◽  
L. Lienenlüke ◽  
S. Storms
Keyword(s):  
Machine Learning ◽  
Position Control ◽  
Learning Algorithm ◽  
Milling Process ◽  
Industrial Robots ◽  
Torque Control ◽  
Feed Forward ◽  
Control Loops ◽  
Model Based ◽  
Machine Learning Approach

Die Lageregelung von konventionellen Industrierobotern ist nicht auf den dynamischen Fräsprozess ausgelegt. Eine Möglichkeit, das Verhalten der Regelkreise zu optimieren, ist eine modellbasierte Momentenvorsteuerung, welche in dieser Arbeit aufgrund vieler Vorteile durch einen Machine-Learning-Ansatz erweitert wird. Hierzu wird die Umsetzung in Matlab und die simulative Evaluation erläutert, die im Anschluss das Potenzial dieses Konzeptes bestätigt.   The position control of conventional industrial robots is not designed for the dynamic milling process. One possibility to optimize the behavior of the control loops is a model-based feed-forward torque control which is supported by a machine learning approach due to many advantages. The implementation in Matlab and the simulative evaluation are explained, which subsequently confirms the potential of this concept.

Experimental Investigation Into Improved Wrapper Control of Hot Strip Steel Rolling Mill Downcoilers

2009 ◽  
Author(s):  
D. Ll. Davies ◽  
J. Watton ◽  
Y. Xue ◽  
G. A. Williams
Keyword(s):  
Rolling Mill ◽  
New Technologies ◽  
Position Control ◽  
Steel Production ◽  
Rolling Process ◽  
Steel Rolling ◽  
Hot Strip ◽  
Accurate Position ◽  
Manufacturing Techniques ◽  
Coiling Process

With increasing international competition in steel production mainly from developing nations, it is important for steel plants to keep up to date with new technologies, and continuously improve on current practices and manufacturing techniques to remain competitive. This paper looks specifically at improvements to the hot rolling mill downcoilers, which is where the strip is coiled at the end of the rolling process. Hydraulic and pneumatic technology is combined to give accurate position control of guide wrappers that aid the initial coiling process. The paper presents an experimental test rig, using an actual wrapper guide, constructed to evaluate the specific design approach.

scholarly journals Research on position offset compensation of underwater manipulator

2021 ◽  
Vol 2125 (1) ◽  
pp. 012008
Author(s):  
Shanbin Ren ◽  
Hui Zhang ◽  
Kai Li ◽  
Yujun Cheng ◽  
Xin Liu ◽  
...  
Keyword(s):  
Curve Fitting ◽  
Position Control ◽  
Kinematic Model ◽  
Compensation Method ◽  
Ansys Analysis ◽  
Underwater Manipulator ◽  
Accurate Position ◽  
Offset Compensation

Abstract A compensation method for end position offset of underwater manipulator is presented in this paper. Firstly, the end deformation of the underwater manipulator is obtained by ANSYS analysis, and then the end position offset equation is obtained by MATLAB curve fitting. Finally, the equation is added to the kinematic model of the underwater manipulator, which improves the accuracy of the kinematic model of the underwater manipulator and lays a foundation for the accurate position control of the underwater manipulator.

Accurate Position Control of a Pneumatic Actuator

1990 ◽  
Vol 112 (4) ◽  
pp. 734-739 ◽  
Author(s):  
Jiing-Yih Lai ◽  
Chia-Hsiang Menq ◽  
Rajendra Singh
Keyword(s):  
Control Strategy ◽  
Pulse Width Modulation ◽  
Position Control ◽  
Integral Control ◽  
Pneumatic Actuators ◽  
Actuator Dynamics ◽  
Position Accuracy ◽  
Modulation Mode ◽  
Nonlinear Mechanical ◽  
Accurate Position

We propose a new control strategy for on-off valve controlled pneumatic actuators and robots with focus on the position accuracy. A mathematical model incorporating pneumatic process nonlinearities and nonlinear mechanical friction has been developed to characterize the actuator dynamics; this model with a few simplifications is then used to design the controller. In our control scheme, one valve is held open and the other is operated under the pulse width modulation mode to simulate the proportional control. An inner loop utilizing proportional-plus-integral control is formed to control the actuator pressure, and an outer loop with displacement and velocity feedbacks is used to control the load displacement. Also, a two staged feedforward force is implemented to reduce the steady state error due to the nonlinear mechanical friction. Experimental results on a single-degree-of-freedom pneumatic robot indicate that the proposed control system is better than the conventional on-off control strategy as it is effective in achieving the desired position accuracy without using any mechanical stops in the actuator.

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