Two-time scale fuzzy logic controller of flexible link robot arm

2003 ◽  
Vol 139 (1) ◽  
pp. 125-149 ◽  
Author(s):  
J. Lin ◽  
F.L. Lewis
Keyword(s):  
Fuzzy Logic ◽  
Time Scale ◽  
Fuzzy Logic Controller ◽  
Robot Arm ◽  
Flexible Link

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.

scholarly journals Desain Fuzzy Logic Controller Untuk Pengendali Pergerakan Mobile Manipulator

2020 ◽  
Vol 1 (01) ◽  
pp. 12-18
Author(s):  
Putri Repina Kesuma ◽  
Tresna Dewi ◽  
RD Kusumanto ◽  
Pola Risma ◽  
Yurni Oktarina
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Mobile Robot ◽  
Fuzzy Logic Controller ◽  
Robot Manipulator ◽  
Human Life ◽  
Agricultural Products ◽  
Mobile Manipulator ◽  
Robot Arm

Technology is developing more and more to facilitate human life. Technology enables automation in all areas of life, and robots are among the most frequently used machines in automation. Robots can help with human work in all fields, including agriculture. A mobile robot manipulator is a combination of a robot arm and a mobile robot so that this type of robot can combine the capabilities of the two robots. This paper discusses the design of a robot manipulator to be used in agriculture to replace farmers in the harvesting of agricultural products, such as tomatoes. This paper presents a mechanical, electrical design and uses the Fuzzy Logic Controller as artificial intelligence. The feasibility of the proposed method is demonstrated by simulation in Mobotsim.

scholarly journals Artificial Intelligent Fuzzy Logic Controller Applied on 6DOF Robot Arm Using LabVIEW and FPGA

2018 ◽  
Vol 3 (5) ◽  
pp. 1
Author(s):  
Ahlam Najm A-Amir ◽  
Hanan A.R. Akkar
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Robot Manipulator ◽  
Robot Arm ◽  
Serial Link ◽  
Artificial Intelligent ◽  
Field Programmable ◽  
Labview Fpga

In this work an efficient Artificial Intelligent Robotic Fuzzy Logic Controller (AIRFC) system have been constructed to control the robot arm. A serial link Robot manipulator with 6 Degree of Freedom (DOF) from DFROBOT of code ROB0036 is used as a case study. A fuzzy logic type1 controller is implemented on LabVIEW to control each joint of the robot arm for nonlinearity measurements and a fuzzy logic type2 controller is applied which is more suitable for uncertainty. The hardware design is implemented and finally downloaded using the Field Programmable Gate Array (FPGA) kit named PCI-7833R from National Instrument. By using the LabVIEW FPGA MODEL the target board can be detected for software implementation of the controllers’ systems. The work shows that in case of type2 fuzzy logic the rise time is less than that of type1 fuzzy logic for the shoulder, wrist roll and the gripper angles and it is higher for base, elbow and wrist pitch angles. The settling time is the same in elbow and wrist pitch angles and for the type2 fuzzy controller it is less for other angles.

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).

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