Dynamic Positioning of An Oceanographic Research Vessel Using Fuzzy Logic Controller in Different Sea States

2021 ◽  
Author(s):  
Kunal Tiwari ◽  
Krishnankutty P.
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Linear Quadratic Regulator ◽  
Research Vessel ◽  
Dynamic Positioning ◽  
Linear Quadratic ◽  
Dynamic Positioning System ◽  
Oceanographic Research ◽  
Thrust Allocation

Abstract A dynamic positioning system is computer controlled system which maintains the positioning and heading of ship by means of active thrust. A DP system consist of sensors, observer, controller and thrust allocation algorithm. The purpose of this paper is to investigate the performance of proportional derivative type fuzzy controller with Mamdani interface scheme for dynamic positioning of an oceanographic research vessel (ORV) by numerical simulation. Nonlinear passive observer is used to filter the noise from the position and orientation. A nonlinear mathematical model of the ORV is subjected to the wave disturbance ranging from calm to phenomenal sea. Robustness and efficiency of the fuzzy logic controller is analysed in comparison with the multivariable proportional integral derivative (PID) and the linear quadratic regulator (LQR) controller. A simplified constrained linear quadratic algorithm is used for thrust allocation. The frequency response of the closed loop system with different controllers is analysed using the bode plot. The stability of controller is established using the Lyapunov criteria.

Fuzzy Logic Controller for Dynamic Positioning of an Offshore Supply Vessel

2017 ◽  
Author(s):  
Kunal N. Tiwari ◽  
Parameswaran Krishnankutty
Keyword(s):  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dynamic Positioning ◽  
Positioning System ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Dynamic Positioning System ◽  
Wave Disturbances ◽  
Control Scheme ◽  
Low Pass

The purpose of this paper is to examine the performance of fuzzy controller applied to a dynamic positioning system of ship by numerical simulation. By definition, dynamic positioning system is computer controlled system which uses the active thrusters to automatically maintain the position and heading of the ship. The proposed control scheme consist of low pass filter in cascade with three proportional derivative type fuzzy controller with Mamdani type inference scheme. Feed-forward compensation decoupling scheme is employed to reduce coupling between sway and yaw. Robustness of control scheme is assessed for Cybership II in presence of wave disturbances.

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 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).

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>

Hybrid Neural-Fuzzy Controller for Motorized Robot Arm

2011 ◽  
Vol 403-408 ◽  
pp. 5068-5075
Author(s):  
Fatma Zada ◽  
Shawket K. Guirguis ◽  
Walied M. Sead
Keyword(s):  
Fuzzy Logic ◽  
Design Methodology ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
System Response ◽  
Robot Arm ◽  
Neural Controller ◽  
Hybrid Controller ◽  
Neural Fuzzy ◽  
Transient And Steady State

In this study, a design methodology is introduced that blends the neural and fuzzy logic controllers in an intelligent way developing a new intelligent hybrid controller. In this design methodology, the fuzzy logic controller works in parallel with the neural controller and adjusting the output of the neural controller. The performance of our proposed controller is demonstrated on a motorized robot arm with disturbances. The simulation results shows that the new hybrid neural -fuzzy controller provides better system response in terms of transient and steady-state performance when compared to neural or fuzzy logic controller applications. The development and implementation of the proposed controller is done using the MATLAB/Simulink toolbox to illustrate the efficiency of the proposed method.

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

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