scholarly journals Comparison of Two Distributed Fuzzy Logic Controllers for Flexible-Link Manipulators

2000 ◽  
Author(s):  
Linda Z. Shi ◽  
Mohamed B. Trabia
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Joint Angle ◽  
Linear Quadratic Regulator ◽  
The Other ◽  
Flexible Link ◽  
Fuzzy Logic Controllers ◽  
Linear Quadratic ◽  
Distributed Controller ◽  
Logic Controllers

Abstract Fuzzy logic control presents a computationally efficient and robust alternative to conventional controllers. An expert in a particular system can usually design a fuzzy logic controller for it easily as can be seen in many applications where fuzzy logic has been already successfully implemented. On the other hand, fuzzy logic controllers are not readily available for flexible-link manipulators. This paper presents two different approaches to design distributed controllers for flexible-link manipulators. The first approach, which is based on observing the performance of flexible manipulators, uses a distributed controller composed of two PD-like fuzzy logic controllers; one controller controls the joint angle while the other controls the tip vibration. The second distributed controller is based on evaluating the importance of the parameters of the system. The most two important parameters, joint and tip point velocities, are grouped together in the same fuzzy logic controller. The other parameters, joint angle and tip point displacement, are used in the second fuzzy logic controller. Both approaches are tuned using nonlinear programming. The paper compares these two approaches with tracking using a linear Quadratic Regulator (LQR).

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 Helicopter Control Using Fuzzy Logic and Narma-L2 Techniques

2020 ◽  
Vol 12 (5) ◽  
pp. 1-14
Author(s):  
Noor Salam Al-Fallooji ◽  
◽  
Maysam Abbod
Keyword(s):  
Fuzzy Logic ◽  
Intelligent System ◽  
Moving Average ◽  
Linear Quadratic Regulator ◽  
Optimization Method ◽  
The Other ◽  
Linear Quadratic ◽  
Lqr Controller ◽  
Artificial Neural Network Ann ◽  
Yaw Angle

Helicopter instability is one of the most limitations that should be addressed in a nonlinear application. Accordingly, researchers are invited to design a robust and reliable controller to obtain a stable system and enhance its overall performance. The present study focuses on the use of the intelligent system in controlling the pitch and yaw angles. This lead to controlling the elevation and the direction of the helicopter. Further to the application of the Linear Quadratic Regulator (LQR) controller, this research implemented the Proportional Integral Derivative (PID), Fuzzy Logic Control (FLC), and Artificial Neural Network (ANN). The results show that FLC achieved a good controllability for both angles, particularly for the pitch angle in comparison to the nonlinear auto regressive moving average (NARMA-L2). Moreover, NARMA-L2 requires further improvement by using, for example, the swarm optimization method to provide better controllability. The PID controller, on the other hand, had a greater capability in controlling the yaw angle in comparison to the other controllers implemented. Accordingly, it is suggested that the integration of PID and FLC may lead to more optimal outcomes.

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.

A survey of Type-2 fuzzy logic controller design using nature inspired optimization

2020 ◽  
Vol 39 (5) ◽  
pp. 6169-6179
Author(s):  
Fevrier Valdez ◽  
Oscar Castillo ◽  
Prometeo Cortes-Antonio ◽  
Patricia Melin
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Optimization Methods ◽  
Fuzzy Logic Controllers ◽  
Logic Control ◽  
Optimal Type ◽  
Logic Controllers

In this paper, we are presenting a survey of research works dealing with Type-2 fuzzy logic controllers designed using optimization algorithms inspired on natural phenomena. Also, in this review, we analyze the most popular optimization methods used to find the important parameters on Type-1 and Type-2 fuzzy logic controllers to improve on previously obtained results. To this end have included a summary of the results obtained from the web of science database to observe the recent trend of using optimization methods in the area of optimal type-2 fuzzy logic control design. Also, we have made a comparison among countries of the network of researchers using optimization methods to analyze the distribution and impact of the papers.

Genetic algorithms with variable mutation rates: Application to fuzzy logic controller design

1997 ◽  
Vol 211 (2) ◽  
pp. 157-167 ◽  
Author(s):  
D T Pham ◽  
D Karaboga
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Mutation Rate ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Mutation Rates ◽  
Fuzzy Logic Controllers ◽  
Delayed System ◽  
Simulation Results ◽  
Logic Controllers

Three variable mutation rate strategies for improving the performance of genetic algorithms (GAs) are described. The problem of optimizing fuzzy logic controllers is used to evaluate a GA adopting these strategies against a GA employing a static mutation regime. Simulation results for a second-order time-delayed system controlled by fuzzy logic controllers (FLCs) obtained using the different GAs are presented.

Inverse Dynamics Based Fuzzy Logic Controller for a Single-Link Flexible Manipulator

2005 ◽  
Author(s):  
Jamil M. Renno
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Joint Angle ◽  
Inverse Dynamics ◽  
Flexible Manipulator ◽  
Flexible Link ◽  
Residual Vibration ◽  
Single Link ◽  
Novel Method ◽  
Motion Parameters

This paper presents a novel method for an inverse dynamics based fuzzy logic controller (FLC) of a single-link flexible manipulator. The control action is distributed between two FLCs: a joint angle controller and a tip controller. A method for varying the ranges of the variables of the two controllers as a function of the motion parameters and the inverse dynamics of the system is presented. Simulation results show that the joint trajectory tracking is accomplished and the residual vibration of the flexible link is suppressed.

scholarly journals LQR and Fuzzy Logic Control for the Three-Area Power System

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8522
Author(s):  
Anna Sibilska-Mroziewicz ◽  
Andrzej Ordys ◽  
Jakub Możaryn ◽  
Pooyan Alinaghi Hosseinabadi ◽  
Ali Soltani Sharif Abadi ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Linear Quadratic Regulator ◽  
Point Of View ◽  
Load Frequency Control ◽  
Linear Quadratic ◽  
Logic Control ◽  
Tie Lines

The three-area power system is widely considered a suitable example to test load frequency control of the distributed generation system. In this article, for such a system, for the power stabilization task, we introduce two controllers: Linear Quadratic Regulator (LQR), which is model-based, and Fuzzy Logic Controller (FLC), which is data-based. The purpose is to compare the two approaches from the point of view of (i) ease of implementation and tuning, and (ii) robustness to changes in the model. The model, together with controls strategies, has been implemented in the MATLAB software. Then, it has been tested for different simulation scenarios, taking into account the disturbances and faulty tie-lines between areas. Various quality measures allow to compare the performance of each control strategy. The comparison in terms of parameter change and load disturbances prompt us to propose suitable metrics and advice notes on the application of each controller.

scholarly journals Design of travel angle control of quanser bench-top helicopter using mamdani-based fuzzy logic controller

2020 ◽  
Vol 17 (2) ◽  
pp. 815 ◽  
Author(s):  
Hasmah Mansor ◽  
Mohamad K. Azmi Mat Esa ◽  
Teddy Surya Gunawan ◽  
Zuriati Janin
Keyword(s):  
Fuzzy Logic ◽  
Closed Loop ◽  
Fuzzy Logic Controller ◽  
Flat Surface ◽  
Linear Quadratic Regulator ◽  
Performance Comparison ◽  
Test Results ◽  
Linear Quadratic ◽  
Integral Controller ◽  
Better Than

<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">This research focuses on travel angle control of a laboratory scale bench-top helicopter developed by Quanser Inc.  Bench top-helicopter is usually used by engineers and researchers to test their designed controllers before applying to the actual helicopter. Bench-top helicopter has the same behavior as the real helicopter, with 3 degree of freedom.  The bench-top helicopter is mounted on a flat surface with two rotors that depends on the voltage supplied to change the direction of the helicopter in 3 different angles. The movement of the helicopter is based on the direction of three-different angles; travel, pitch and yaw angles. The existing Linear Quadratic Regulator-Integral controller used by Quanser Inc has some limitations in terms of tracking capability and settling time; therefore this research is proposed. The objective of this research is to develop Mamdani-based Fuzzy Logic Controller for travel angle control of bench-top helicopter. Performance comparison has been done with the existing Linear Quadratic Regulator-Integral controller in both simulation and hardware. From the test results, it was found that the performance of Fuzzy Logic Controller is better than LQR-I controller especially for closed-loop simulation at desired angle of 30°. The percentage of overshoot of the Fuzzy Logic Controller has been improved from the existing controller which is 4.912% compared to 7.002% for LQR-I.</span>

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