Intelligent motion control of robotic mechanism

UiTM, College of Engineering (2024) Intelligent motion control of robotic mechanism. Bulletin. College of Engineering, Shah Alam.

Abstract

Robotic mechanisms are increasingly used in various industries, including agriculture, automotive, aerospace, medical, and logistics, due to their controlled features. With the increasing demand for repetitive high-speed and high-precision operations, intelligent control coupled with adaptive motion strategy is crucial to address the issues of excessive vibration and energy usage. These are important for economic justification besides several motion constraint parameters such as end-effector travel distance, speed, and acceleration during the robot's operations. These parameters are important to avoid workpiece breakage, machine tool fatigue, excessive vibration, and energy usage for an extended period of repetitive operations. This research study investigates models and methods for vibration suppression and energy optimisation of a DC motor-driven robotic mechanism. The prototypes used are six degrees of freedom (DOF) robotic arm manipulator and three degrees of freedom underactuated robotics crane with the developed computer algorithm. The under-actuated crane mechanism consists of a double link system where rotation motions consist of two parts, each belonging to respective links. Link 1 is a rotation motion due to the DC motor embedded with the encoder. Link 2 is the swing motion affected by link 1.

Metadata

Item Type: Monograph (Bulletin)
Creators:
Creators
Email / ID Num.
UiTM, College of Engineering
UNSPECIFIED
Contributors:
Contribution
Name
Email / ID Num.
Contributor
Azman, Nur Azareena
UNSPECIFIED
Contributor
Ayub, Muhammad Azmi
UNSPECIFIED
Subjects: L Education > LG Individual institutions > Asia > Malaysia > Universiti Teknologi MARA
T Technology > TJ Mechanical engineering and machinery
Divisions: Universiti Teknologi MARA, Shah Alam > College of Engineering
Journal or Publication Title: DIGEST Volume 1, 2024
ISSN: 2805-573X
Keywords: Digest, Engineering, UiTM
Date: January 2024
URI: https://ir.uitm.edu.my/id/eprint/135152
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