Fuzzy Rule Formulation Algorithm for Fuzzy Logic-Based 6-DOF Robot Arm Controller

2018 ◽  
Vol 22 (5) ◽  
pp. 718-724
Author(s):  
Alexander C. Abad ◽  
Dino Dominic F. Ligutan ◽  
Argel A. Bandala ◽  
Elmer P. Dadios ◽  
◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Rule ◽  
Arm Movement ◽  
Robotic Arm ◽  
Robot Arm ◽  
Dynamic Movement ◽  
Actual Response ◽  
Actual Control ◽  
Frictional Effects

A fuzzy logic-based controller with fuzzy rule formulation algorithm on software and actual control for a 6-DOF robotic arm was implemented. A robotic arm with 4-DOF attached a 2-DOF gripper serves as the testing platform. The actual robotic arm was characterized and the parameters are used for the simulator to mimic actual response. The fuzzy logic controller is then implemented to the simulated robotic arm and was then implemented to the actual robotic arm to control its movement. The new features are as follows: (1) Implementation of simulated weight and frictional effects of dynamic robot arm movement, (2) formulation and justification of reduced fuzzy rules for control and (3) addition of a path-partitioning algorithm to further enhance the dynamic movement of the robotic arm.

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.

Robotic Arm Movement Optimization Using Soft Computing

2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Surender Kumar ◽  
Kavita Rani ◽  
V. K. Banga
Keyword(s):  
Optimal Control ◽  
Genetic Algorithms ◽  
Soft Computing ◽  
Target Position ◽  
Arm Movement ◽  
Degree Of Freedom ◽  
Robotic Arm ◽  
Robot Arm ◽  
Soft Computing Techniques ◽  
Simulation Time

<p class="Text">Robots are commonly used in industries due to their versatility and efficiency. Most of them operating in that stage of the manufacturing process where the maximum of robot arm movement is utilized. Therefore, the robots arm movement optimization by using several techniques is a main focus for many researchers as well as manufacturer. The robot arm optimization is This paper proposes an approach to optimal control for movement and trajectory planning of a various degree of freedom in robot using soft computing techniques. Also evaluated and show comparative analysis of various degree of freedom in robotic arm to compensate the uncertainties like movement, friction and settling time in robotic arm movement. Before optimization, requires to understand the robot's arm movement i.e. its kinematics behavior. With the help of genetic algorithms and the model joints, the robotic arm movement is optimized. The results of robotic arm movement is optimal at all possible input values, reaches the target position within the simulation time.</p>

Fuzzy Logic and Intelligence System

2000 ◽  
Vol 4 (5) ◽  
pp. 319-320
Author(s):  
Hyung Lee-Kwang ◽  
◽  
Ju-Jang Lee
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Rough Set ◽  
Intelligent Systems ◽  
Fuzzy Logic Controller ◽  
Fuzzy Rule ◽  
Wavelet Neural Network ◽  
Classification Method ◽  
Inference System

These papers are originally published in the proceedings of Korea fuzzy logic and intelligent systems society (KFIS) fall conference in 1999. Eight papers are selected for this special issue. Major topics of them are fuzzy theory, neural network, inference system, intelligent controller, etc. In this issue, Seihwan Park and Hyung Lee-Kwang extend the concept of fuzzy hypergraph to type-2 fuzzy hypergraph using type-2 fuzzy sets. It has not only the same properties of hypergraphs but also the extended properties of them. It is also shown that interval valued fuzzy hypergraph is a special case of type-2 fuzzy hypergraph. Jung-Heum Yon, Yong-Taek Kim, Jae-Yong Seo and Hong-Tae Jeon design an efficient neural network called dynamic multidimensional wavelet neural network. It can perform an effective dynamic mapping with less dimensions of the input signal. These features show one way to compensate the weakness of the diagonal recurrent neural network and feedforward wavelet neural network. Yigon Kim, Yang Hee Jung and Young Chel Bae propose a new method for diagnosis of insulation aging using wavelet. It measures the partial discharge on-line from data acquisition system and analyses it using wavelet to acquire 21) patterns. They design a neuro-fuzzy model that diagnoses an electrical equipment using the data. Byung-Jae Choi, Seong-Woo Kwak and Byung Kook Kim develop an adaptive fuzzy logic controller. A sole input fuzzy variable is used to simplify the design procedure and the switching hyperplane of sliding mode control is used to improve the adaptability. Myung-Geun Chun, Keun-Chang Kwak and Jeong-Woong Ryu show an efficient fuzzy rule generation scheme for adaptive network-based fuzzy inference system using the conditional fuzzy c-means and fuzzy equalization methods. They apply this method to the truck backer-upper control and Box-Jenkins modeling problem. Daijin Kim proposes a new data classification method based on the tolerant rough set that extends the existing equivalent rough set. Twostage classification method is used. All data are classified by using the lower approximation at the first stage and then the non-classified data at the first stage are classified again by using the rough membership functions obtained from the upper approximation set. Min-Soeng Kim, Sun-Gi Hong and Ju-Jang Lee incorporate the Q-learning algorithm into the fuzzy logic controller. Modified fuzzy rule is used for the incorporation. As a result, a fuzzy logic controller is obtained that can learn through experience. Dong Hwa Kim designs a new 2-DOF PID controller and applies it to the operating data based transfer function of Gun-san Gas turbine in Korea. We hope that this issue can be helpful to readers and we appreciate professor Kaoru Hirota for his interest and support for the publication.

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 A fuzzy rule based approach for islanding detection in grid connected inverter systems

2021 ◽  
Vol 11 (6) ◽  
pp. 4759
Author(s):  
Naima Ikken ◽  
Nour-Eddine Tariba ◽  
Abdelhadi Bouknadel ◽  
Ahmed Haddou ◽  
Hafsa El Omari ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Distribution System ◽  
Power Plants ◽  
Distribution Systems ◽  
Fuzzy Logic Controller ◽  
Detection System ◽  
Fuzzy Rule ◽  
Islanding Detection ◽  
Detection Zone ◽  
Rule Based Approach

<span lang="EN-US">Islanding is when an area of the electrical distribution system is isolated from the electrical system while being powered by distributed generators. An important condition for the interconnection of power plants and distribution systems is the ability of the power plant to detect islands. The presented and proposed method is a combination of best active sandia frequency shift (SFS) method with the intelligent fuzzy logic controller, which has been tested in distributed production using the island detection function. And the choice to improve the method by fuzzy logic control (FLC) is retained, as this process is more effective in decreasing the non-</span><span lang="EN-US">detection zone (NDZ) and in further improving the efficiency of the islanding detection system. This paper proposes a new active islanding detection technique controlled by a fuzzy logic controller, for grid connected photovoltaic (PV) inverters. In addition, the efficiency and performance of the proposed method strategy for islanding detection has been analyzed and tested in the various situations of the network. In addition, the results of the simulations with the <span lang="EN-US">power </span><span lang="EN-US">simulation (</span>PSIM) software will be provided to illustrate the main conclusions and the development of the control. Thus, will be used to show the feasibility and validity of the proposed new algorithm.</span>

Fuzzy Logic Controller Design of a Single Stage Fluid Valve Based Robotic Arm

2021 ◽  
Author(s):  
Akin Tatoglu ◽  
Claudio Campana ◽  
James Nolan ◽  
Gary Toloczko
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Controller Design ◽  
Single Stage ◽  
Robotic Arm
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