Implementation and experimental study of a fuzzy logic controller for dc motors

1995 ◽  
Vol 26 (1) ◽  
pp. 93-96 ◽  
Author(s):  
C.M. Lim
Keyword(s):  
Experimental Study ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motors

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

scholarly journals Active tremor control in human-like hand tremor using fuzzy logic

2021 ◽  
Vol 24 (1) ◽  
pp. 108
Author(s):  
Hafiz Bin Jamaludin ◽  
Azizan As'arry ◽  
R. Musab ◽  
Khairil Anas Md Rezali ◽  
Raja Mohd Kamil Bin Raja Ahmad ◽  
...  
Keyword(s):  
Experimental Study ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Initial Step ◽  
Daily Activities ◽  
Hand Tremor ◽  
Hybrid Controller ◽  
A Value ◽  
Power Spectral ◽  
Reduction Percentage

<span>Tremor<span>is the vibration in sinusoidal orientation that is experienced regularly by a person with Parkinson’s disease (PD), which disturbs their daily activities. One solution that may be used to counter this tremor effect is by developing an active tremor control system in LabVIEW for linear voice coil actuator (LVCA), where the system uses proportional (P) controller and various types of fuzzy logic controller (FLC) as a hybrid controller to reduce tremor vibration. From this research, it can be concluded that the best controller for tremor reduction is the P+FLC 1<sup>st</sup> set of rules, compared to P+FLC 2<sup>nd</sup> set of rules, and P controller only, with the highest percentage of 88.39% of tremor reduction with the actual tremor vibration of PD patients as the reference result. The P+FLC 2<sup>nd</sup> set of rules has the highest percentage of tremor reduction with a value of 86.81%, whereas P controller only has the highest tremor reduction percentage of 67.10%. This percentage of tremor reduction is based on the power spectral density (PSD) values, in which it represents the intensity of the tremor vibration. This experimental study can be used as an initial step for researchers and engineers to design and develop an anti-tremor device in the future.</span></span>

scholarly journals Optimal Tuning of Fuzzy Logic Controller Based Speed Control of DC Motor

2021 ◽  
Vol 19 (1) ◽  
pp. 77-80
Author(s):  
Mohsin A. Koondhar ◽  
Muhammad U. Keerio ◽  
Rameez A. Talani ◽  
Kamran A. Samo ◽  
Muhammad S. Bajwa ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Speed Control ◽  
Dc Motor ◽  
Motor Speed ◽  
Dc Motors ◽  
Manual Adjustment ◽  
Control Application ◽  
Installation Time ◽  
Transient And Steady State

Fuzzy logic controller (FLC) has become popular in the speed control application of DC motors with automatic adjustment function. In this article, the performance of a specific FLC controlled DC motor is studied. The exceed speed is observed with a stabilization time, thus confirming the FLC behavior. Therefore, FLC must be set to obtain the required performance by applying appropriate expert rules, the minimum overshoot and installation time can be maintained within the required values. With the help of FLC, the manual adjustment function is gradually eliminated, and the intelligent adjustment function is at the center position, and the performance is satisfactory. FLC DC motor speed control is implemented in MATLAB environment. The results show that the FLC method has the smallest bypass, smallest transient and steady-state error, and shows higher FLC efficiency as compared with other conventional controllers.

scholarly journals Fuzzy Logic Controller sebagai Penentu Gerak Mobile Robot Pembasmi Hama

2020 ◽  
Vol 1 (01) ◽  
pp. 19-24
Author(s):  
Muhammad Ridho Kenawas ◽  
Pola Risma ◽  
Tresna Dewi ◽  
Selamet Muslimin ◽  
Yurni Oktarina
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
High Speed ◽  
Fuzzy Logic Controller ◽  
Pulse Width Modulation ◽  
Robot Motion ◽  
Crop Failure ◽  
Driving System ◽  
Dc Motors ◽  
Autonomous Decision

A mobile robot is one of the solutions to overcome crop failure caused by chili pests. The mobile robot discussed in this paper is used to spray pesticide liquid into chili plant stems to prevent pests attack on the plants. This paper discusses the design of pesticide spraying robot motion with the application of Fuzzy Logic Controller. This robot employment is expected to reduce farmers' workload and to help to produce a good harvest.  Robot motions are divided into two conditions, which can be controlled by remote control as a controller (manual) and by means of a sensor (automatic). Mobile robot movements have a significant impact on navigation and the design of the driving system. Robot speed is controller by adjusting Pulse Width Modulation of DC motors attached to the robots' wheel, which set to be  90 for slow and 220  for high speed. The Fuzzy Logic Controller in this mobile robot functions as an autonomous decision-making driver to detect obstacles in front of the mobile robot and the targeted stems.

scholarly journals Dissimilarity Clustering Algorithm for Designing the PID-like Fuzzy Controllers

2021 ◽  
Vol 45 (1) ◽  
pp. 267-286
Author(s):  
Essam Natsheh
Keyword(s):  
Fuzzy Logic ◽  
Clustering Algorithm ◽  
Fuzzy Logic Controller ◽  
Type Model ◽  
Performance Study ◽  
Process Industries ◽  
Research Fields ◽  
Dc Motors ◽  
Models Comparison ◽  
Improved Accuracy

Fuzzy logic controller is one of the most prominent research fields to improve efficiency for process industries, which usually stick to the conventional proportional-integral-derivative (PID) control. The paper proposes an improved version of the three-term PID-like fuzzy logic controller by removing the necessity of having user-defined parameters in place for the algorithm to work. The resulting non-parametric three-term dissimilarity-based clustering fuzzy logic controller algorithm was shown to be very efficient and fast. The performance study was conducted by simulation on armature-controlled and field-controller DC motors, for linguistic type and Takagi-Sugeno-Kang (TSK) models. Comparison of the created algorithm with fuzzy c-means algorithm resulted in improved accuracy, increased speed and enhanced robustness, with an especially high increase for the TSK type model.

scholarly journals Real-time implementation of a novel hybrid fuzzy sliding mode control of a BLDC motor

2019 ◽  
Vol 10 (3) ◽  
pp. 1167
Author(s):  
Ali Mousmi ◽  
Ahmed Abbou ◽  
Yassine El Houm
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Hybrid Control ◽  
Sliding Mode ◽  
Fast Response ◽  
Bldc Motor ◽  
Tracking Accuracy ◽  
Brushless Dc Motors ◽  
Brushless Dc ◽  
Dc Motors

<span lang="EN-US">This paper presents a novel hybrid control of a BLDC motor using a mixed sliding mode and fuzzy logic controller. The objective is to build a fast and robust controller which overcome classical controllers’ inconveniences and exploit the fast response of brushless dc motors characterized by an intense torque and fast response time. First the paper study pros and cons of both sliding mode and fuzzy logic controllers. Then the novel controller and its stability demonstration are presented. Finally the proposed controller method is used for the speed control of a BLDC motor 3KW. The obtained results are compared with those of a fuzzy logic and a conventional sliding mode controller. It allows to show performance of the proposed controller in terms of speed response and reaction against disturbances, which is improved more than 5 times without losing stability or altering tracking accuracy</span>

scholarly journals The Mobile Robot Control in Obstacle Avoidance Using Fuzzy Logic Controller

2020 ◽  
Vol 5 (3) ◽  
pp. 334-351
Author(s):  
M. Khairudin ◽  
R. Refalda ◽  
S. Yatmono ◽  
H. S. Pramono ◽  
A. K. Triatmaja ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Experimental Work ◽  
Fuzzy Logic Controller ◽  
Input Voltage ◽  
Robot System ◽  
Dc Motors ◽  
Robot Systems

A very challenging problem in mobile robot systems is mostly in obstacle avoidance strategies. This study aims to describe how the obstacle avoidance system on mobile robots works. This system is designed automatically using fuzzy logic control (FLC) developed using Matlab to help the mobile robots to avoid a head-on collision. The FLC designs were simulated on the mobile robot system. The simulation was conducted by comparing FLC performance to the proportional integral derivative (PID) controller. The simulation results indicate that FLC works better with lower settling time performance. To validate the results, FLC was used in a mobile robot system. It shows that FLC can control the velocity by braking or accelerating according to the sensor input installed in front of the mobile robot. The FLC control system functions as ultrasonic sensor input or a distance sensor. The input voltage was simulated with the potentiometer, whereas the output was shown by the velocity of DC motor. This study employed the simulation work in Simulink and Matlab, while the experimental work used laboratory scale of mobile robots. The results show that the velocity control of DC motors with FLC produces accurate data, so the robot could avoid the existing obstacles. The findings indicate that the simulation and the experimental work of FLC for mobile robot in obstacle avoidance are very close.

Improving the Performance of a Vibration Neutraliser by Controlling Its Stiffness and Damping

2000 ◽  
Author(s):  
M. J. Brennan ◽  
M. R. F. Kidner
Keyword(s):  
Experimental Study ◽  
Fuzzy Logic ◽  
Real Time ◽  
Fuzzy Logic Controller ◽  
Feedback System ◽  
Real Time Control ◽  
Velocity Feedback ◽  
Time Control ◽  
Operational Frequency ◽  
Stiffness And Damping

Abstract This paper is concerned with improving the performance of a vibration neutraliser (absorber) by making it adaptive. To achieve this, the stiffness and damping of the device has to be controlled so that the impedance of the neutraliser is optimised at its operational frequency. The results of an experimental study are presented where real-time control of such a device is demonstrated. The stiffness is adjusted by changing the geometry, and damping is controlled with a velocity feedback system. Both these actions are achieved using a fuzzy logic controller.

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