scholarly journals A Self-Tuning Fuzzy Logic Controller for Aircraft Roll Control System

2013 ◽  
Vol 2 (6) ◽  
pp. 181-188 ◽  
Author(s):  
Omur Akyazi ◽  
Mehmet Ali Usta ◽  
Adem Sefa Akpinar
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Roll Control ◽  
Self Tuning

Fuzzy Logic Controller Designing of an Active Roll Control System for Medium and Large Size Vehicles

2011 ◽  
Vol 110-116 ◽  
pp. 4845-4855 ◽  
Author(s):  
Peiman Hajishafieiha
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Roll Angle ◽  
Torsional Stiffness ◽  
Roll Control ◽  
Large Size ◽  
Handling Characteristics ◽  
Active Roll Control ◽  
Roll Axis

The roll / ride trade-off is a long-standing challenge to vehicle dynamicists. Achieving better ride performance almost inevitably leads to increased roll of the vehicle. This roll motion, mostly induced by maneuvering, leads to undesirable handling characteristics and subsequently higher risk of rollover. This paper analyses the use of an Active Roll Control (ARC) system with a Fuzzy Logic Controller (FLC) for improving the handling without sacrificing the ride comfort. The logic for reducing the roll angle of the vehicle is to have some forces exerted by linear actuators on the suspension system, depending on the velocity and steering angle of the vehicle. These forces create a moment about the roll axis which decreases the roll angle. The proposed Fuzzy logic controller is a feedback controller which outputs the correcting roll moment about the roll axis. The effects of employing such a control system are evaluated through computer simulation. Torsional stiffness of the chassis is then taken into consideration to account for unique properties of large-size vehicles. Simulation results with Fuzzy logic controller are very promising and show that the roll performance is significantly improved compared to the vehicle without ARC.

scholarly journals RESEARCH OF LIQUID LEVEL CONTROL SYSTEM / SKYSČIO LYGIO VALDYMO SISTEMOS TYRIMAS

2015 ◽  
Vol 7 (3) ◽  
pp. 317-322
Author(s):  
Dominykas Beištaras
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Controller ◽  
Liquid Level ◽  
Water Tank ◽  
Level Control ◽  
Level Control System ◽  
Filling Time ◽  
Control System Model ◽  
Liquid Level Control

This paper presents liquid level control system model and analysis of dynamic characteristics. The system consists of scalar controlled induction motor drive, fuzzy logic controller, water tank and centrifugal pump. Simulink models of water tank, pump and controller are presented. The simulation of the system shows that the use of fuzzy logic controller reduces valve opening time and reservoir filling time. Nagrinėjamas skysčio lygio valdymo sistemos imitacinių modelių sudarymas, analizuojamos dinaminės charakteristikos. Valdymo sistema sudaryta iš skaliariniu būdu valdomos dažninės elektros pavaros su neraiškiosios logikos reguliatoriumi, vandens rezervuaro ir išcentrinio siurblio. Sudaryti rezervuaro, siurblio ir reguliatoriaus Simulink modeliai. Atlikus imitacijas gauta nedimensinė siurblio charakteristika, apibūdinanti siurblio veikimą, esant bet kokiam sukimosi greičiui. Nustatyta, kad sistemoje su neraiškiosios logikos reguliatoriumi vožtuvas yra atidaromas greičiau nei sistemoje su proporcinguoju integraliniu (PI) reguliatoriumi, ir todėl sumažinama rezervuaro pripildymo trukmė.

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 Experimental simplified rule of self tuning fuzzy logic-model reference adaptive speed controller for induction motor drive

2020 ◽  
Vol 20 (3) ◽  
pp. 1653
Author(s):  
M.Z. Ismail ◽  
M.H.N. Talib ◽  
Z. Ibrahim ◽  
J. Mat Lazi ◽  
Z. Rasin
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Tuning Parameter ◽  
Model Reference ◽  
Wide Range ◽  
Speed Performance ◽  
Self Tuning ◽  
Model Reference Adaptive

<span>Fuzzy logic controller (FLC) has shown excellent performance in dealing with the non-linearity and complex dynamic model of the induction motor. However, a conventional constant parameter FLC (CPFL) will not be able to provide–good coverage performance for a wide speed range operation with a single tuning parameter. Therefore, this paper proposed a self tuning mechanism FLC approach by model reference adaptive controller (ST-MRAC) to continuously allow to adjust the parameters. Due to real time hardware application, the dominant rules selection method for simplified rules has been implemented as part of the reducing computational burden. Experiment results validate a good performance of the ST-MRAC compared to the CPFL for the   speed performance in terms of the wide range of operations and disturbance showed remarkable performance.</span>

Sign in / Sign up

Export Citation Format

Share Document