Low level position control for 4-DOF arm robot using fuzzy logic controller and 2-DOF PID controller

2021 ◽  
Author(s):  
Mohamed Fawzy El-Khatib ◽  
Shady A. Maged
Keyword(s):  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Low Level

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.

Development of Servo Drive Positioning Control System Using PID Controller and Fuzzy Logic Controller

2021 ◽  
Vol 26 (6) ◽  
pp. 583-588
Author(s):  
Zaw Myo Naing ◽  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Settling Time ◽  
Fuzzy Pid ◽  
Servo Drive ◽  
Positioning Control ◽  
Fuzzy Pid Controller

Servo drives are one of the most widely utilized devices in various mechanical systems and industrial applications to provide precise position control. The study of servo driver produc-tiveness and performance index is the important task. In this work, PID controller and fuzzy log-ic controller (FLC) were developed to control the position of a DC servo drive. The MATLAB Simulink program was investigated and implemented to calculate the values of servo drive pa-rameters, and a scheme for simulating the operation of a servo drive using different controllers was presented. A mathematical model of a DC servo drive for a positioning control system has been proposed. The control characteristics of the PID controller, fuzzy logic controller and fuzzy PID controller are compared. The simulation results have shown that the PID controller allows for an overshoot of about 1 % with a settling time of about 4 sec. The use of the fuzzy PID con-troller reduces the maximum overshoot to 1 % and decreases the settling time to 2 sec. As a re-sult, the fuzzy PID controller allows for better performance and efficiency compared to other controllers.

scholarly journals Development of a DSP Microcontroller-Based Fuzzy Logic Controller for Heliostat Orientation Control

2020 ◽  
Vol 10 (5) ◽  
pp. 1598
Author(s):  
Eugenio Salgado-Plasencia ◽  
Roberto V. Carrillo-Serrano ◽  
Manuel Toledano-Ayala
Keyword(s):  
Fuzzy Logic ◽  
Digital Signal Processor ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Low Cost ◽  
Angular Position ◽  
Digital Signal ◽  
Orientation Control ◽  
Dc Motors

This paper describes the design and implementation of a heliostat orientation control system based on a low-cost microcontroller. The proposed system uses a fuzzy logic controller (FLC) with the Center of Sums defuzzification method embedded on a dsPIC33EP256MU806 Digital Signal Processor (DSP), in order to modify the orientation of a heliostat by controlling the angular position of two DC motors connected to the axes of the heliostat. The FLC is compared to a traditional Proportional-Integral-Derivative (PID) controller to evaluate the performance of the system. Both the FLC and PID controller were designed for the position control of the heliostat DC motors at no load, and then they were implemented in the orientation control of the heliostat using the same controller parameters. The experimental results show that the FLC has a better performance and flexibility than a traditional PID controller in the orientation control of a heliostat.

scholarly journals MATHEMATICAL ALGORITHM OF FUZZY LOGIC CONTROLLER FOR MULTILEVEL INVERTER CREATING VERTICAL DIVIDED VOLTAGE

2019 ◽  
Vol 59 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Erol Can
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Pid Controller ◽  
Output Voltage ◽  
Fuzzy Logic Controller ◽  
Boost Converter ◽  
Multilevel Inverter ◽  
Logic Control ◽  
Multi Level

A 9-level inverter with a boost converter has been controlled with a fuzzy logic controller and a PID controller for regulating output voltage applications on resistive (R) and inductive (L), capacitance (C). The mathematical model of this system is created according to the fuzzy logic controlling new high multilevel inverter with a boost converter. The DC-DC boost converter and the multi-level inverter are designed and explained, when creating a mathematical model after a linear pulse width modulation (LPWM), it is preferred to operate the boost multi-level inverter. The fuzzy logic control and the PID control are used to manage the LPWM that allows the switches to operate. The fuzzy logic algorithm is presented by giving necessary mathematical equations that have second-degree differential equations for the fuzzy logic controller. After that, the fuzzy logic controller is set up in the 9-level inverter. The proposed model runs on different membership positions of the triangles at the fuzzy logic controller after testing the PID controller. After the output voltage of the converter, the output voltage of the inverter and the output current of the inverter are observed at the MATLAB SIMULINK, the obtained results are analysed and compared. The results show the demanded performance of the inverter and approve the contribution of the fuzzy logic control on multi-level inverter circuits.

scholarly journals Online Position Control Performance Improving Applying Incremental Fuzzy Logic Controller

2018 ◽  
Vol 248 ◽  
pp. 02005
Author(s):  
Dirman Hanafi ◽  
Mohamed Najib Ribuan ◽  
Wan HamidahWan Abas ◽  
Hidayat ◽  
Elmy Johana ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Motor Performance ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Peak Time ◽  
Control Performance ◽  
Position Control System

This paper presents the online control system application for improving the DC motor performance. DC motor widely used in industries and many appliances. For this aim fuzzy logic controller is applied. The type of fuzzy controller use is an incremental fuzzy logic controller (IFLC). The IFLC is developed by using MATLAB Simulink Software and implemented in online position control system applying RAPCON board as a platform. The experimental results produced the best gains of the IFLC are 1.785, 0.0056955 and 0.01 for error gain (GE), gain of change error (GCE) and gain of output (GCU) respectively. Its produce smaller rise time, peak time, 0% overshoot and smaller settling time. Beside that the IFLC response also able to follow the set point. The controller response parameters values are also acceptable. It means that the IFLC suitable to be use for improving the position control system performance.

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