Anti-Swing Adaptive Fuzzy Controller for an Overhead Crane With Hoisting

2004 ◽  
Author(s):  
Jamil M. Renno ◽  
Mohamed B. Trabia ◽  
Kamal A. F. Moustafa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
Overhead Crane ◽  
Fuzzy Logic Controllers ◽  
Adaptive Fuzzy Controller ◽  
Overhead Cranes ◽  
Logic Control ◽  
Novel Method

This paper presents a novel method for adaptive anti-swing fuzzy logic control for overhead cranes with hoisting. The control action is distributed between three fuzzy logic controllers (FLC’s): trolley controller, hoist controller, and anti-swing controller. A method for varying the ranges of the variables of the three controllers as a function of the crane’s parameters and/or motion variables is presented. Simulation examples show that the proposed controller can successfully drive overhead cranes under various operating conditions.

Inverse Dynamics-Based Fuzzy Logic Control of a Projectile Smart Fin

2005 ◽  
Author(s):  
Mohamed B. Trabia ◽  
Surya Kiran Parimi ◽  
Woosoon Yim
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Inverse Dynamics ◽  
Operating Conditions ◽  
Attractive Alternative ◽  
Fuzzy Logic Controllers ◽  
Logic Control ◽  
Novel Approach ◽  
External Moment ◽  
Element Approach

A smart fin for a subsonic projectile should be able to produce maneuvering force and moment that can control its rotation during flight. Piezoelectric actuator is an attractive alternative to usual hydraulic actuators due to its simplicity. The cantilever-shaped actuator can also be fully enclosed within the hollow fin. It has an end fixed to the rotation axle of the fin while the other end is pinned at the tip of the fin. A dynamic model of the system, including external moment due to aerodynamic effects, is obtained using the finite element approach. This paper presents a novel approach for automatically creating fuzzy logic controllers for the fin. This approach uses the inverse dynamics of the smart fin system to determine the ranges of the variables of the controllers. Simulation results show that the proposed controller can successfully drive smart fin under various operating conditions.

A Single Phase Anti-Swing Fuzzy Logic Controller for an Overhead Crane With Hoisting

2006 ◽  
Author(s):  
Mohamed B. Trabia ◽  
Jamil M. Renno ◽  
Kamal A. F. Moustafa
Keyword(s):  
Fuzzy Logic ◽  
Single Phase ◽  
Fuzzy Logic Controller ◽  
Inverse Dynamics ◽  
Operating Conditions ◽  
Overhead Crane ◽  
Fuzzy Logic Controllers ◽  
Overhead Cranes ◽  
Novel Approach ◽  
Logic Controllers

This paper presents a novel approach for automatically creating anti-swing fuzzy logic controllers for overhead cranes with hoisting. This approach uses the inverse dynamics of the overhead crane to determine the ranges of the variables of the controllers. The control action is distributed among three fuzzy logic controllers (FLCs): travel controller, hoist controller, and anti-swing controller. Simulation examples show that the proposed controller can successfully drive overhead cranes under various operating conditions.

scholarly journals DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller

Jurnal Teknik ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Sumardi Sadi
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Logic Control ◽  
Control Command ◽  
Arduino Uno

DC motors are included in the category of motor types that are most widely used both in industrial environments, household appliances to children's toys. The development of control technology has also made many advances from conventional control to automatic control to intelligent control. Fuzzy logic is used as a control system, because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this research is to study and apply the fuzzy mamdani logic method to the Arduino uno microcontroller, to control the speed of a DC motor and to control the speed of the fan. The research method used is an experimental method. Global testing is divided into three, namely sensor testing, Pulse Width Modulation (PWM) testing and Mamdani fuzzy logic control testing. The fuzzy controller output is a control command given to the DC motor. In this DC motor control system using the Mamdani method and the control system is designed using two inputs in the form of Error and Delta Error. The two inputs will be processed by the fuzzy logic controller (FLC) to get the output value in the form of a PWM signal to control the DC motor. The results of this study indicate that the fuzzy logic control system with the Arduino uno microcontroller can control the rotational speed of the DC motor as desired.

Interval Type-2 Fuzzy Logic Control of NM70 Shape Memory Actuator

2014 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic ◽  
Shape Memory ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Logic Control ◽  
Interval Type ◽  
Nonlinear Plant

The main aim of this article is to present the usage of type-2 fuzzy logic controller to control a shape memory actuator. To enhance real-time performance simplified interval fuzzy sets were used. The algorithm was implemented in the ATmega32 microcontroller. The dedicated PC application was also built. The fuzzy logic controller type-2 was tested experimentally by controlling position of the shape memory alloy actuator NM70 which despite its small size distinguishes itself by its strength. The obtained results confirmed that type-2 fuzzy controller performed efficiently with a difficult to control nonlinear plant. The research also proved that interval type-2 controllers, which are a simplified version of the general type-2 controllers, are very efficient. They can handle uncertainties without increasing drastically the computational complexity. Experimental data comparison of the fuzzy logic controller type-2 with type-1 clearly indicates the superiority of the former, especially in reducing overshooting.

scholarly journals Optimal Slip Ratio Based Fuzzy Control of Acceleration Slip Regulation for Four-Wheel Independent Driving Electric Vehicles

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Guodong Yin ◽  
Shanbao Wang ◽  
Xianjian Jin
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Angular Acceleration ◽  
Slip Rate ◽  
Wheel Slip ◽  
Slip Ratio ◽  
Logic Control

To improve the driving performance and the stability of the electric vehicle, a novel acceleration slip regulation (ASR) algorithm based on fuzzy logic control strategy is proposed for four-wheel independent driving (4WID) electric vehicles. In the algorithm, angular acceleration and slip rate based fuzzy controller of acceleration slip regulation are designed to maintain the wheel slip within the optimal range by adjusting the motor torque dynamically. In order to evaluate the performance of the algorithm, the models of the main components related to the ASR of the four-wheel independent driving electric vehicle are built in MATLAB/SIMULINK. The simulations show that the driving stability and the safety of the electric vehicle are improved for fuzzy logic control compared with the conventional PID control.

scholarly journals Fuzzy Logic Control of a Ball on Sphere System

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Seyed Alireza Moezi ◽  
Ehsan Zakeri ◽  
Yousef Bazargan-Lari ◽  
Mahmood Khalghollah
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Systems ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Nonlinear Dynamic Systems ◽  
Underactuated System ◽  
Control Problems ◽  
Logic Control ◽  
Good State ◽  
Simulation Results

The scope of this paper is to present a fuzzy logic control of a class of multi-input multioutput (MIMO) nonlinear systems called “system of ball on a sphere,” such an inherently nonlinear, unstable, and underactuated system, considered truly to be two independent ball and wheel systems around its equilibrium point. In this work, Sugeno method is investigated as a fuzzy controller method, so it works in a good state with optimization and adaptive techniques, which makes it very attractive in control problems, particularly for such nonlinear dynamic systems. The system’s dynamic is described and the equations are illustrated. The outputs are shown in different figures so as to be compared. Finally, these simulation results show the exactness of the controller’s performance.

Comparison of Two Distributed Fuzzy Logic Controllers for Two-Link Rigid-Flexible Manipulator

2003 ◽  
Author(s):  
Linda Z. Shi ◽  
Mohamed B. Trabia
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Vertical Plane ◽  
Flexible Manipulator ◽  
Computationally Efficient ◽  
Fuzzy Logic Controllers ◽  
Distributed Structure ◽  
Logic Control ◽  
Angular Velocities ◽  
Logic Controllers

Fuzzy logic control presents a computationally efficient and robust alternative to conventional controllers. While experts can easily design fuzzy logic controllers (FLC’s) for many applications, some systems such as multi-link flexible manipulators, which have many variables and complex behavior, offer challenges to fuzzy logic control. An earlier work, [1], presented two distributed FLC’s for a single-link flexible manipulator. This paper extends that work to the area of two-link rigid-flexible manipulator that moves in a vertical plane where the gravity field is active. The first distributed structure, which is based on observing the performance of the manipulator, uses three PD-like FLC’s. The first two FLC’s control joint angles and joint angular velocities while the third controls the tip vibration. The second distributed structure is based on evaluating the importance degrees of the system output variables of the system by randomly varying its inputs. Variables with the same rank of the importance degree are grouped together and variables with less importance degrees may be deleted to simplify the design of the controller. The fuzzy rules of FLC’s in the two structures are selected to mimic the performance of comparable linear controllers. The parameters in both structures are tuned using nonlinear programming to obtain better performance. The two distributed structures are simulated and compared.

GA-Based Fuzzy Logic Control for a Smart Fin of a Projectile

2007 ◽  
Author(s):  
Venkat Mudupu ◽  
Mohamed B. Trabia ◽  
Woosoon Yim ◽  
Paul Weinacht
Keyword(s):  
Fuzzy Logic ◽  
System Identification ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Operating Conditions ◽  
Piezoelectric Bimorph ◽  
Logic Control ◽  
Identification Technique ◽  
Simulation Results ◽  
Design And Testing

This paper presents the design and testing of a smart fin for a subsonic projectile. The smart fin is activated using a piezoelectric bimorph with a substrate that is completely enclosed within the fin. A linear model of the actuator and fin system is created using the frequency response identification technique within MATLAB System Identification Toolbox. A procedure for designing a GA-based fuzzy logic controller for the fin is presented. Experimental and simulation results show that the proposed controller achieved the fin angle control under different operating conditions.

Anti-Swing Trajectory Control of an Overhead Crane

2011 ◽  
Author(s):  
E. H. K. Fung ◽  
H. F. Yu ◽  
K. H. Suen ◽  
A. T. Leung
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Equations Of Motion ◽  
Overhead Crane ◽  
Transportation Time ◽  
Swing Angle ◽  
Total Potential ◽  
Logic Control ◽  
Set Up

Imprecise positioning and swing of load of overhead crane cause prolonged transportation time. Some researchers tried to achieve suppression of swing angle and fast transfer simultaneously. But, the hoisting motion is usually ignored which can cause greater swing angle. Hence, a physical 2-DOF overhead crane model which consists of horizontal motion and hoisting motion is set up for this study. The total kinetic energy and the total potential energy are derived to obtain dynamic equations of motion by using Lagrangian method. Secondly, fuzzy logic control (FLC) has been adopted to control positioning of horizontal and hoisting motion and to suppress swing angle during transportation. Moreover, to minimize total transportation time, proportional (P) controller is added to the system forming the switching P+FLC controller. Finally, the proposed methods are evaluated by simulations and experiments. The overall results show that fuzzy logic controller combined with P controller (P+FLC) can effectively reduce the transportation time with a little increase in the swing angle.

scholarly journals An improved 1-φ rectifier system using fuzzy logic control with 3-φ variable frequency drive

2018 ◽  
Vol 7 (2.7) ◽  
pp. 520
Author(s):  
M Kiran Kumar ◽  
SK Almaj ◽  
K S. Srikanth
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Output Frequency ◽  
Variable Frequency Drive ◽  
Dc Voltage ◽  
Motor Current ◽  
Logic Control ◽  
Voltage Ripple

A 3-Φ VFD steam fed from a 1-Φ AC supply. To stop more stresses in the components within the drive and within the input supply,  the drive output power should be restricted. To beat this problem, several VFD makers decided that drive to be de-rated. As often as possible, the drive’s output frequency is limited, supported the dc voltage ripple hence the DC capacitors aren’t overstressed. Through the tradional technique decrement of strain within the DC Capacitors, it doesn’t consider the stresses in other parts of the drive, particularly the diodes at the input and terminal blocks of input. During this paper, brand new fuzzy controller based technique for the protection of the drive the motor   current with FLC is projected. The motor  current is shown to possess info relating the stresses in numerous elements of the VFD together with the diodes at the input, terminal blocks of the input, and therefore the Dc capacitors. The o/p power is projected to be restricted by decreasing the o/p frequency supported the avg and ripple abundancy of the quadrature axis current rather than the dc voltage ripple. To prove this conception, a comparison is made between fuzzy logic controller based technique employing a less power VFD fed from a 1-Φ ac, and the conventional dc voltage ripple based frequency technique.                                                                                                                                                                  

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