Oil Whip Elimination Using Fuzzy Logic Controller

2015 ◽  
Vol 138 (6) ◽  
Author(s):  
A. S. Dimitri ◽  
J. Mahfoud ◽  
A. El-Shafei
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Control Action ◽  
Test Rig ◽  
Logic Control ◽  
Oil Whip ◽  
Simple Geometry ◽  
Wide Range

Oil whip is a self-excited subsynchronous vibration which limits the range of operating speed of journal bearings (JBs). JBs have wide range of applications due to their high loading capacity, simple geometry, and lubrication. When the speed of rotation increases, the oil whip instability is excited with a frequency corresponding to the rotor critical speed which causes excessive undesirable vibration. A solution for this instability is implemented through this paper. The control action is implemented through a new integrated bearing device. The bearing consists of JB and electromagnetic actuator (EMA). The oil whip control action is applied through the EMA. A fuzzy logic control algorithm is developed and experimentally applied to a rotor test rig. The controller is suitable to deal with the problems of uncertainties and nonlinearity. The experimental results show the ability of the developed controller to eliminate the oil whip instability when applied to a test rig which simulates industrial rotor through an integrated bearing prototype which was designed and manufactured.

Oil Whip Elimination Using Fuzzy Logic Controller

2014 ◽  
Author(s):  
A. S. Dimitri ◽  
J. Mahfoud ◽  
A. El-Shafei
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Control Action ◽  
Test Rig ◽  
Logic Control ◽  
Oil Whip ◽  
Simple Geometry ◽  
Wide Range

Oil whip is a self-excited sub-synchronous vibration which limits the range of operating speed of Journal Bearings (JB). JB have wide range of applications due to their high loading capacity, simple geometry, and lubrication. When the speed of rotation increases, the oil whip instability is excited with a frequency corresponding to the rotor critical speed which causes excessive undesirable vibration. A solution for this instability is implemented through this paper. The control action is implemented through a new integrated bearing device. The bearing consists of JB and Electromagnetic Actuator (EMA). The oil whip control action is applied through the EMA. A fuzzy logic control algorithm is developed and experimentally applied to a rotor test rig. The fuzzy logic controller is suitable to deal with problems of uncertainties and non-linearity. The experimental results show the ability of the developed fuzzy logic controller to eliminate the oil whip instability when applied to a test rig which simulates industrial rotor through an integrated bearing prototype which was designed and manufactured.

A contribution to the identification in fuzzy-logic control

1990 ◽  
Vol 55 (4) ◽  
pp. 951-963 ◽  
Author(s):  
Josef Vrba ◽  
Ywetta Purová
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Automatic Generation ◽  
Linguistic Variable ◽  
Fuzzy Subset ◽  
Input Output ◽  
Logic Control ◽  
Correlation Tables

A linguistic identification of a system controlled by a fuzzy-logic controller is presented. The information about the behaviour of the system, concentrated in time-series, is analyzed from the point of its description by linguistic variable and fuzzy subset as its quantifier. The partial input/output relation and its strength is expressed by a sort of correlation tables and coefficients. The principles of automatic generation of model statements are presented as well.

Permanent Magnet Chatter Absorber with Fuzzy Logic Control

2009 ◽  
Vol 147-149 ◽  
pp. 290-295 ◽  
Author(s):  
Bogdan Broel-Plater ◽  
Stefan Domek ◽  
Arkadiusz Parus
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Permanent Magnets ◽  
Practical Experience ◽  
High Energy ◽  
Logic Control ◽  
Machine Operators

The paper deals with semi-active chatter absorber based on an electrodynamic transducer built around high-energy permanent magnets. Also, a fuzzy logic control system for the absorber control system has been designed. The principal advantage of fuzzy control is the possibility to implement practical experience gained by machine operators in the control algorithm. Hence, the possibility of factoring such quantities, as vibrations experienced by selected points of the machine-tool, and sound emitted by working machine into the analyzed chatter absorber fuzzy control system has been studied in the paper. The control system has been tested by way of simulation with the use of the process and cutting force models.

Comparison of a Fuzzy Logic Controller With a P + D Control Law

1989 ◽  
Vol 111 (2) ◽  
pp. 128-137 ◽  
Author(s):  
S. Daley ◽  
K. F. Gill
Keyword(s):  
Fuzzy Logic ◽  
Attitude Control ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Good Control ◽  
Control Law ◽  
Dynamic Coupling ◽  
Process Knowledge ◽  
Logic Control ◽  
Limited Process

A study is described that compares the performance of a self-organizing fuzzy logic control law (SOC) with that of the more traditional P + D algorithm. The multivariate problem used for the investigation is the attitude control of a flexible satellite that has significant dynamic coupling of the axes. It is demonstrated that the SOC can provide good control, requires limited process knowledge and compares favorably with the P + D algorithm.

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.

scholarly journals Control of a dc motor using fuzzy logic control algorithm

2017 ◽  
Vol 36 (2) ◽  
pp. 594 ◽  
Author(s):  
I. H. Usoro ◽  
U. T. Itaketo ◽  
M. A. Umoren
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Control Algorithm ◽  
Dc Motor ◽  
Logic Control

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.

Fuzzy Logic Control of a Laboratory Magnetic Levitation System

2003 ◽  
Author(s):  
V. Ram Mohan Parimi ◽  
Piyush Jain ◽  
Devendra P. Garg
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Magnetic Levitation ◽  
Rate Of Change ◽  
Control Laboratory ◽  
Logic Control ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
And Control

This paper deals with the Fuzzy Logic control of a Magnetic Levitation system [1] available in the Robotics and Control Laboratory at Duke University. The laboratory Magnetic Levitation system primarily consists of a metallic ball, an electromagnet and an infrared optical sensor. The objective of the control experiment is to balance the metallic ball in a magnetic field at a desired position against gravity. The dynamics and control complexity of the system makes it an ideal control laboratory experiment. The student can design their own control schemes and/or change the parameters on the existing control modes supplied with the Magnetic Levitation system, and evaluate and compare their performances. In the process, they overcome challenges such as designing various control techniques, choose which specific control strategy to use, and learn how to optimize it. A Fuzzy Logic control scheme was designed and implemented to control the Magnetic Levitation system. Position and rate of change of position were the inputs to Fuzzy Logic Controller. Experiments were performed on the existing Magnetic Levitation system. Results from these experiments and digital simulation are presented in the paper.

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