Fuzzy Rule Formulation Algorithm for Fuzzy Logic-Based 6-DOF Robot Arm Controller-Reference-Cited by-同舟云学术

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

Published:2018-09-20 Issue:5 Volume:22 Page:718-724
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Abad Alexander C.,Ligutan Dino Dominic F.,Bandala Argel A.,Dadios Elmer P., ,

Abstract

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.

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

Reference15 articles.

1. A. B. Rehiara, “Kinematics of AdeptThree Robot Arm,” S. Goto ed., Robot Arms, InTech, DOI: 10.5772/17732, 2011. https://www.intechopen.com/books/robot-arms/kinematics-of-adeptthree-robot-arm [accessed January 29, 2018]

2. D. D. Ligutan et al., “Design and implementation of a fuzzy logic-based joint controller on a 6-DOF robot arm with machine vision feedback,” 2017 Computing Conf., London, pp. 249-257, 2017.

3. H. P. H. Anh, K. K. Ahn, and N. T. Nam, “Modeling Identification of the Nonlinear Robot Arm System Using MISO NARX Fuzzy Model and Genetic Algorithm,” S. Goto ed., Robot Arms, InTech, DOI: 10.5772/16422, 2011. https://www.intechopen.com/books/robot-arms/modeling-identification-of-the-nonlinear-robot-arm-system-using-miso-narx-fuzzy-model-and-genetic-al [accessed January 29, 2018]

4. A. A. Khalate, G. Leena, and G. Ray, “An Adaptive Fuzzy Controller for Trajectory Tracking of Robot Manipulator,” Intelligent Control and Automation, pp. 364-370, 2011.

5. E. P. Dadios and D. J. Williams, “Multiple fuzzy logic systems: A controller for the flexible pole-cart balancing problem,” Proc. of the IEEE Robotics and Automation Int. Conf., Minneapolis, Minnesota USA, ICRA, pp. 2276-2281, 1996.