Enhancing the Feedforward –Feedback Controller for Nonlinear Overhead Crane Using Fuzzy logic controller

AbstractDifferent industrial applications frequently use overhead cranes for moving and lifting huge loads. It applies to civil construction, metallurgical production, rivers, and seaports. The primary purpose of this paper is to control the motion/position of the overhead crane using a PID controller using Genetic Algorithms (GA) and Bee Algorithms (BA) as optimization tools. Moreover, Fuzzy Logic modified PID Controller is applied to obtain better controller parameters. The mathematical model uses an analytical method, and the PID model employs Simulink in MATLAB. The paper presents the PID parameters determination with a different approach. The development of membership functions, fuzzy rules employ the Fuzzy Logic toolbox. Both inputs and outputs use triangular membership functions. The result shows that the optimized value of the PID controller with the Ziegler-Nichols approach is time-consuming and will provide only the initial parameters. However, PID parameters obtained with the optimization method using GA and BA reached the target values. The results obtained with the fuzzy logic controller (0.227% overshoot) show improvement in overshoot than the conventional PID controller (0.271% overshoot).

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

Dynamic Systems and Control, Parts A and B ◽

10.1115/imece2006-13837 ◽

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.

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Anti-Swing Trajectory Control of an Overhead Crane

Volume 7: Dynamic Systems and Control; Mechatronics and Intelligent Machines, Parts A and B ◽

10.1115/imece2011-63527 ◽

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.

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Active Control of Thermally Induced Vibrations in Smart Structure Instrumented with Piezoelectric Materials

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.612.169 ◽

2014 ◽

Vol 612 ◽

pp. 169-174 ◽

Cited By ~ 2

Author(s):

Anshul Sharma ◽

C.K. Susheel ◽

Rajeev Kumar ◽

V.S. Chauhan

Keyword(s):

Finite Element ◽

Fuzzy Logic ◽

Negative Feedback ◽

Fuzzy Logic Controller ◽

Coupling Effect ◽

Shear Deformation Theory ◽

Smart Structure ◽

Feedback Controller ◽

Mechanical Coupling ◽

Degenerated Shell Element

In this paper, a finite element model of piezolaminated composite shell structure is developed using nine-noded degenerated shell element. The stiffness, mass and thermo-electro-mechanical coupling effect is incorporated in finite element modeling using first order shear deformation theory and linear piezoelectric theory. The sensor voltage is calculated using the same formulation and fuzzy logic controller is used to calculate the actuator voltage. The fuzzy logic controller is designed as double input-single output (DISO) system using 49 If-Then rules. The performance of fuzzy logic controller is compared with convention constant-gain negative feedback controller. The simulation results illustrate the superiority of fuzzy logic controller over constant-gain negative feedback controller.

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Autonomous Overhead Crane System Using a Fuzzy Logic Controller

Journal of Vibration and Control ◽

10.1177/1077546304042038 ◽

2004 ◽

Vol 10 (9) ◽

pp. 1255-1270 ◽

Cited By ~ 18

Author(s):

F. Omar ◽

F. Karray ◽

O. Basir ◽

L. Yu

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic Controller ◽

Load Transfer ◽

Fuzzy Controller ◽

Accurate Estimation ◽

Small Scale ◽

Overhead Crane ◽

Overhead Cranes ◽

Highly Nonlinear ◽

System States

This paper pertains to advanced automation of the load transfer process using overhead cranes. Overhead cranes are widely used in various areas of industry, including manufacturing, construction, shipping, etc. Load transfer operations using overhead cranes have to be performed fast and safely. As such, these operations are handled by expert operators however, the demand for an automatic consistent and reliable crane operation is on the rise. The crane–load system is highly nonlinear and time-varying, hence, solutions considering model-base approaches may lead to a complicated controller structure. Such a controller may require accurate estimation of the crane system parameters. In this paper we present a new fuzzy logic controller for overhead crane operation. The fuzzy controller is designed based on knowledge of an expert crane operator, and does not require any parameter estimation. It mimics the operator behavior by using the same crane–load system states that are realized by the operator. These states are the trolley position error and the load sway angle. The fuzzy controller action, on the other hand, is the desired trolley speed. The proposed controller is implemented and tested on a small-scale overhead crane. Experimental results show robust operation of the fuzzy controller as compared with that of a conventional controller.

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Design a Fuzzy Logic Controller for a Rotary Flexible Joint Robotic Arm

MATEC Web of Conferences ◽

10.1051/matecconf/201815001011 ◽

2018 ◽

Vol 150 ◽

pp. 01011 ◽

Cited By ~ 1

Author(s):

Jamaludin Jalani ◽

Suman Jayaraman

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic Controller ◽

Feedback Controller ◽

Robotic Arm ◽

Flexible Joint ◽

Simulation And Experiment

The purpose of this research is to design a fuzzy logic feedback controller (FLC) in order to control a desired tip angle position a rotary flexible joint robotic arm. The FLC is also employed to dampen the vibration emanated from a rotary flexible joint robotic arm when reaching a desired tip angle position. The performance of FLC is tested in simulation and experiment. It is found that the FLC is successfully designed, applied and tested. The results show that fuzzy logic controller performed satisfactorily control a desired tip angle position and reduce the oscillations.

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Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

ACMIT Proceedings ◽

10.33555/acmit.v3i1.43 ◽

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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A Self Learning Fuzzy Logic Controller for Ship Steering System

Iraqi Journal for Electrical And Electronic Engineering ◽

10.33762/eeej.2012.79716 ◽

2012 ◽

Vol 8 (1) ◽

pp. 25-34

Author(s):

Ammar A. Aldair

Keyword(s):

Fuzzy Logic ◽

Fuzzy Logic Controller ◽

Steering System ◽

Ship Steering ◽

Self Learning

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STABILISASI TEGANGAN KELUARAN BUCK CONVERTER DENGAN METODE FUZZY LOGIC CONTROLLER

JURNAL ELTEK ◽

10.33795/eltek.v16i2.104 ◽

2018 ◽

Vol 16 (2) ◽

pp. 125

Author(s):

Oktriza Melfazen

Keyword(s):

Fuzzy Logic ◽

Steady State ◽

Rise Time ◽

Fuzzy Logic Controller ◽

Buck Converter ◽

Settling Time

Buck converter idealnya mempunyai keluaran yang stabil, pemanfaatandaya rendah, mudah untuk diatur, antarmuka yang mudah dengan pirantiyang lain, ketahanan yang lebih tinggi terhadap perubahan kondisi alam.Beberapa teknik dikembangkan untuk memenuhi parameter buckconverter. Solusi paling logis untuk digunakan pada sistem ini adalahmetode kontrol digital.Penelitian ini menelaah uji performansi terhadap stabilitas tegangankeluaran buck converter yang dikontrol dengan Logika Fuzzy metodeMamdani. Rangkaian sistem terdiri dari sumber tegangan DC variable,sensor tegangan dan Buck Converter dengan beban resistif sebagaimasukan, mikrokontroler ATMega 8535 sebagai subsistem kontroldengan metode logika fuzzy dan LCD sebagai penampil keluaran.Dengan fungsi keanggotaan error, delta error dan keanggotaan keluaranmasing-masing sebanyak 5 bagian serta metode defuzzifikasi center ofgrafity (COG), didapat hasil rerata error 0,29% pada variable masukan18V–20V dan setpoint keluaran 15V, rise time (tr) = 0,14s ; settling time(ts) = 3,4s ; maximum over shoot (%OS) = 2,6 dan error steady state(ess) = 0,3.

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