Fuzzy Logic Control of the End-Point Vibration in an Experimental Flexible Beam

2004 ◽  
Vol 10 (4) ◽  
pp. 493-506 ◽  
Author(s):  
A. Jnifene ◽  
W Andrews
Keyword(s):  
Fuzzy Logic ◽  
Strain Gage ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Angular Displacement ◽  
Angular Position ◽  
Rule Base ◽  
Flexible Beam ◽  
End Point ◽  
Logic Control

This paper is concerned with the design and implementation of a fuzzy logic controller (FLC) to control the end-point vibration in a single flexible beam mounted on a two-degrees-of-freedom platform. The angular position of the hub and the signal from a strain gage mounted on the beam are used as the two inputs to the FLC. In order to add more damping, the strain gage signal is combined with the hub angular velocity represented by the output of a tachometer attached to the motor shaft. We discuss how to build the rule base for the flexible beam based on the relation between the angular displacement of the hub and the end-point deflection, as well as the effect of different scaling gains on the performance of the FLC. We present several experimental results showing the effectiveness of the FLC in reducing the end-point vibration of the flexible beam.

Fuzzy Logic Control for an Integrated System of a Micro-Manipulator with a Single Flexible Beam

2004 ◽  
Vol 10 (5) ◽  
pp. 755-776 ◽  
Author(s):  
N. G. Chalhoub ◽  
B. A. Bazzi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Angular Displacement ◽  
Digital Simulation ◽  
Linear Quadratic Regulator ◽  
Integrated System ◽  
Flexible Beam ◽  
Linear Quadratic ◽  
End Effector ◽  
Micro Manipulator

The use of lightweight robotic manipulators in advanced assembly and manufacturing applications is hindered by the end-effector positional inaccuracies induced by the structural deformations of the arm. To address this problem, a macro- and micro-manipulator system is considered herein. Three rigid and flexible motion controllers, consisting of an integral plus state feedback controller (ISFC), linear quadratic regulator with an integral action (LQI) and a fuzzy logic controller (FLC), have been implemented in this study. The performances of these controllers are compared based on achieving zero steady-state error in the rigid body angular displacement of the beam, damping out the unwanted vibrations, rendering the end-effector insensitive to the vibrations of the arm, and avoiding excessive control torque requirements. The digital simulation results demonstrate the superiority of the FLC over the ISFC and LQI in damping out the vibrations of the beam and reducing the gripper positional inaccuracies while requiring relatively smaller control torques. Furthermore, the results clearly demonstrate the robustness of the FLC to significant variations in the payload mass.

scholarly journals MODELING AND SIMULATION OF ROTOR FLUX OBSERVER BASED INDIRECT VECTOR CONTROL OF INDUCTION MOTOR DRIVE USING FUZZY LOGIC CONTROL

2014 ◽  
pp. 241-246
Author(s):  
B. MOULI CHANDRA ◽  
S.TARA KALYANI
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Rule Base ◽  
Flux Observer ◽  
Logic Control ◽  
Rotor Flux ◽  
Proportional Integral Controller ◽  
Inductor Motor

The indirect vector controlled inductor motor (IM) drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of fuzzy logic control scheme applied to a two d-q current components model of an induction motor. A Fuzzy logic Controller is developed with the help of knowledge rule base for efficient and robust control. The performance of Fuzzy Logic Controller is compared with that of the PI controller with rotor flux observer in terms of the settling time and dynamic response to sudden load changes. The harmonic pattern of the output current is evaluated for both fixed gain proportional integral controller and the Fuzzy Logic based controller. The performance of the IM drive has been analyzed under steady state and transient conditions. Simulation results of both the controllers are presented for comparison.

scholarly journals Control of Flexible Joint Manipulator via Reduced Rule-Based Fuzzy Control with Experimental Validation

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Mojtaba Rostami Kandroodi ◽  
Mohammad Mansouri ◽  
Mahdi Aliyari Shoorehdeli ◽  
Mohammad Teshnehlab
Keyword(s):  
Fuzzy Logic ◽  
Experimental Validation ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Angular Position ◽  
Rule Base ◽  
Flexible Joint ◽  
Novel Structure ◽  
Flexible Joint Manipulator ◽  
Derivatives Of

A novel structure of fuzzy logic controller is presented for trajectory tracking and vibration control of a flexible joint manipulator. The rule base of fuzzy controller is divided into two sections. Each section includes two variables. The variables of first section are the error of tip angular position and the error of deflection angle, while the variables of second section are derivatives of mentioned errors. Using these structures, it would be possible to reduce the number of rules. Advantages of proposed fuzzy logic are low computational complexity, high interpretability of rules, and convenience in fuzzy controller. Implementing of the fuzzy logic controller on Quanser flexible joint reveals efficiency of proposed controller. To show the efficiency of this method, the results are compared with LQR method. In this paper, experimental validation of proposed method is presented.

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

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.

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 Design and Lyapunov Stability Analysis of a Fuzzy Logic Controller for Autonomous Road Following

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Yi Fu ◽  
Howard Li ◽  
Mary Kaye
Keyword(s):  
Fuzzy Logic ◽  
Stability Analysis ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Intelligent Vehicles ◽  
Intelligent Vehicle ◽  
Rule Base ◽  
Control Laws ◽  
Robotic Vehicle ◽  
Road Following

Autonomous road following is one of the major goals in intelligent vehicle applications. The development of an autonomous road following embedded system for intelligent vehicles is the focus of this paper. A fuzzy logic controller (FLC) is designed for vision-based autonomous road following. The stability analysis of this control system is addressed. Lyapunov's direct method is utilized to formulate a class of control laws that guarantee the convergence of the steering error. Certain requirements for the control laws are presented for designers to choose a suitable rule base for the fuzzy controller in order to make the system stable. Stability of the proposed fuzzy controller is guaranteed theoretically and also demonstrated by simulation studies and experiments. Simulations using the model of the four degree of freedom nonholonomic robotic vehicle are conducted to investigate the performance of the fuzzy controller. The proposed fuzzy controller can achieve the desired steering angle and make the robotic vehicle follow the road successfully. Experiments show that the developed intelligent vehicle is able to follow a mocked road autonomously.

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 Center of Pressure Feedback for Controlling the Walking Stability Bipedal Robots using Fuzzy Logic Controller

2018 ◽  
Vol 8 (5) ◽  
pp. 3678
Author(s):  
Afrizal Mayub ◽  
Fahmizal Fahmizal
Keyword(s):  
Fuzzy Logic ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Center Of Pressure ◽  
Bipedal Robots ◽  
Bipedal Robot ◽  
Position Information ◽  
Pressure Feedback ◽  
The Stability ◽  
Foot Pad

This paper presents a sensor-based stability walk for bipedal robots by using force sensitive resistor (FSR) sensor. To perform walk stability on uneven terrain conditions, FSR sensor is used as feedbacks to evaluate the stability of bipedal robot instead of the center of pressure (CoP). In this work, CoP that was generated from four FSR sensors placed on each foot-pad is used to evaluate the walking stability. The robot CoP position provided an indication of walk stability. The CoP position information was further evaluated with a fuzzy logic controller (FLC) to generate appropriate offset angles to be applied to meet a stable situation. Moreover, in this paper designed a FLC through CoP region's stability and stable compliance control are introduced. Finally, the performances of the proposed methods were verified with 18-degrees of freedom (DOF) kid-size bipedal robot.<br /><br />

Approximated Simplest Fuzzy Logic Controlled Shunt Active Power Filter for Current Harmonic Mitigation

2013 ◽  
pp. 155-171
Author(s):  
Rambir Singh ◽  
Asheesh K. Singh ◽  
Rakesh K. Arya
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Active Power Filter ◽  
Pi Controller ◽  
Active Power ◽  
Rule Base ◽  
Shunt Active Power Filter ◽  
Harmonic Compensation ◽  
Power Filter ◽  
Harmonic Mitigation

This paper examines the size reduction of the fuzzy rule base without compromising the control characteristics of a fuzzy logic controller (FLC). A 49-rule FLC is approximated by a 4-rule simplest FLC using compensating factors. This approximated 4-rule FLC is implemented to control the shunt active power filter (APF), which is used for harmonic mitigation in source current. The proposed control methodology is less complex and computationally efficient due to significant reduction in the size of rule base. As a result, computational time and memory requirement are also reduced significantly. The control performance and harmonic compensation capability of proposed approximated 4-rule FLC based shunt APF is compared with the conventional PI controller and 49-rule FLC under randomly varying nonlinear loads. The simulation results presented under transient and steady state conditions show that dynamic performance of approximated simplest FLC is better than conventional PI controller and comparable with 49-rule FLC, while maintaining harmonic compensation within limits. Due to its effectiveness and reduced complexity, the proposed approximation methodology emerges out to be a suitable alternative for large rule FLC.

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