scholarly journals Fuzzy logic controller design for PUMA 560 robot manipulator

2020 ◽  
Vol 9 (2) ◽  
pp. 73
Author(s):  
Abdel-Azim S. Abdel-Salam ◽  
Ibrahim N. Jleta
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Controller Design ◽  
Robot Manipulator ◽  
Tracking Error ◽  
Pid Controllers ◽  
Fuzzy Logic Controllers ◽  
Better Than ◽  
Computed Torque

The dynamic model of the robot manipulator contain from equations, these equations are nonlinear and contained from variations parameters due to variations in load, friction, and disturbance. The conventional computed torque (PD and PID) controllers are not highly suitable for nonlinear, complex, time-variant systems with delay. In this paper, the fuzzy logic controllers (FLC) has been used because it is efficient tools for control of nonlinear and uncertain parameters systems. This paper aims to design a fuzzy logic controller for position control of a PUMA 560 robot manipulator. Based on simulation results we conclude that the performance of the fuzzy logic controller in term of position tracking error in case of disturbance or load is better than the conventional computed torque (PD-CTC and PID-CTC) controllers.

A survey of Type-2 fuzzy logic controller design using nature inspired optimization

2020 ◽  
Vol 39 (5) ◽  
pp. 6169-6179
Author(s):  
Fevrier Valdez ◽  
Oscar Castillo ◽  
Prometeo Cortes-Antonio ◽  
Patricia Melin
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Optimization Methods ◽  
Fuzzy Logic Controllers ◽  
Logic Control ◽  
Optimal Type ◽  
Logic Controllers

In this paper, we are presenting a survey of research works dealing with Type-2 fuzzy logic controllers designed using optimization algorithms inspired on natural phenomena. Also, in this review, we analyze the most popular optimization methods used to find the important parameters on Type-1 and Type-2 fuzzy logic controllers to improve on previously obtained results. To this end have included a summary of the results obtained from the web of science database to observe the recent trend of using optimization methods in the area of optimal type-2 fuzzy logic control design. Also, we have made a comparison among countries of the network of researchers using optimization methods to analyze the distribution and impact of the papers.

scholarly journals Modelling and Simulation of Stepper Motor For Position Control Using LabVIEW

1970 ◽  
Vol 5 (1.) ◽  
Author(s):  
Ahmet Mehmet Karadeniz ◽  
Malek Alkayyali ◽  
Péter Tamás Szemes
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Bond Graph ◽  
Industrial Applications ◽  
Modelling And Simulation ◽  
Stepper Motor ◽  
Stepping Motor ◽  
Better Than

This paper presents hybrid stepper motor (is a type of stepping motor) modelling and simulation which is widely used a kind of motor in industrial applications. In this study, the stepper motor was modelled using bond graph technique and simulation for desired position was executed on LabVIEWgraphical interface. Then, firstly a convenient PID controller was designed for position, speed and current and PID close loopresponse was obtained for position control. Then, PID parameters for each controller were arranged separately to obtain good response Secondly, Fuzzy Logic controller applied to the system and its response was obtained. Finally, both responses are compared. According to comparison, it was observed that Fuzzy Logic controller’s response is better than PID’s. (In this paper, all shown responses were observed for 120 degree desired position)

scholarly journals PID and Fuzzy Logic Controller Design for Balancing Robot Stabilization

2018 ◽  
pp. 1-10
Keyword(s):  
Fuzzy Logic ◽  
Tilt Angle ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Controller Design ◽  
Point Of View ◽  
Relative Advantage ◽  
Balancing Robot ◽  
Time Required

This paper addresses the problem of position control and stabilization for the two wheeled balancing robot. A mathematical model is derived based on the robot’s position and tilt angle and a fuzzy logic control is proposed for the balancing robot control. The fuzzy logic controller performance is compared with a conventional PID controller to show the difference between them. Both controllers were tested on the balancing robot in simulation using MATLAB software and the results were put together for a comparative point of view. The simulations shows a relative advantage for the fuzzy logic controller over the conventional PID controller especially in reducing the time required for stabilization which takes about 2 seconds and almost without overshoot while in the PID case the robot will have about 10% overshoot in position and about 20 degrees in tilt angle.

Genetic algorithms with variable mutation rates: Application to fuzzy logic controller design

1997 ◽  
Vol 211 (2) ◽  
pp. 157-167 ◽  
Author(s):  
D T Pham ◽  
D Karaboga
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Mutation Rate ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Mutation Rates ◽  
Fuzzy Logic Controllers ◽  
Delayed System ◽  
Simulation Results ◽  
Logic Controllers

Three variable mutation rate strategies for improving the performance of genetic algorithms (GAs) are described. The problem of optimizing fuzzy logic controllers is used to evaluate a GA adopting these strategies against a GA employing a static mutation regime. Simulation results for a second-order time-delayed system controlled by fuzzy logic controllers (FLCs) obtained using the different GAs are presented.

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.

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